Packages & Setup

# install.packages(c("tidyverse","purrr","R.matlab","readxl","dplyr"))
library(readxl);
library(purrr)
library(tidyverse);
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## ✔ ggplot2   3.5.0     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
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library(tibble)
library(knitr);
library(gtsummary)
library(kableExtra)
## 
## Attaching package: 'kableExtra'
## 
## The following object is masked from 'package:dplyr':
## 
##     group_rows
library(lme4)
## Loading required package: Matrix
## 
## Attaching package: 'Matrix'
## 
## The following objects are masked from 'package:tidyr':
## 
##     expand, pack, unpack

GTSUMMARY THEME

# my_theme <-
#   list(
#     "tbl_summary-str:default_con_type" = "continuous2",
#     "tbl_summary-str:continuous_stat" = c(
#       "{median} ({p25} - {p75})",
#       "{mean} ({sd})",
#       "{min} - {max}"
#     ),
#     "tbl_summary-str:categorical_stat" = "{n} / {N} ({p}%)",
#     "style_number-arg:big.mark" = "",
#     "tbl_summary-fn:percent_fun" = function(x) style_percent(x, digits = 3)
#   )
# my_theme <-
#   list()
# gtsummary::set_gtsummary_theme(my_theme)
gtsummary::set_gtsummary_theme(theme_gtsummary_journal("jama"))
## Setting theme `JAMA`
## Setting theme `JAMA`
# reset_gtsummary_theme()

load table

# excel_dir <-"M:/jsalminen/GitHub/par_EEGProcessing/src/_data/MIM_dataset/_studies/04162024_MIM_YAOAN89_antsnormalize_iccREMG0p4_powpow0p3_skull0p01/cluster/icrej_5/12/spec_data/group_spec/psd_calcs/fooof_kinematics_table.xlsx";
excel_dir <-"M:/jsalminen/GitHub/par_EEGProcessing/src/_data/MIM_dataset/_studies/04232024_MIM_YAOAN89_antsnorm_dipfix_iccREMG0p4_powpow0p3_skull0p01_15mmrej/cluster/icrej_5/11/spec_data/group_spec/psd_calcs/fooof_kinematics_table_nans.xlsx";
eegt <- read_excel(excel_dir,sheet="Sheet1") 

get unique entries

clusters = unique(eegt$cluster_id);
subjects = unique(eegt$subj_char);
groups = unique(eegt$group_char);
kin_measures = c('mean_APexc_COV','mean_APexc_mean','mean_MLexc_COV','mean_MLexc_mean','mean_StepDur','mean_UDexc_COV','mean_UDexc_mean','mean_StanceDur','mean_GaitCycleDur','mean_PeakUpDownVel_mean');
kin_title_chars = c("AP Exc. COV","AP Exc. Mean","ML Exc. COV","ML Exc. Mean","Step Dur.","UD Exc. COV","UD Exc Mean","Stance Dur.","Gait Cycle Dur.","Peak UD Vel. Mean")
kin_inds_plot = c(1:length(kin_measures));
eeg_measures = c('theta_avg_power','alpha_avg_power','beta_avg_power','beta_div_theta','theta_div_beta','log_beta_div_theta','log_theta_div_beta','aperiodic_exp','aperiodic_offset');
eeg_title_chars = c("**THETA**","**ALPHA**","**BETA**","**BETA/THETA**","**THETA/BETA**","**log10(BETA/THETA)**","**log10(THETA/BETA)**","**AP exp**","**AP offset**");
eeg_inds_plot = c(4:7);

get speeds only

eegt <- filter_at(eegt,vars('cond_char'), any_vars(. %in% c('0.25','0.5','0.75','1.0')))
flat_speeds = unique(eegt$cond_char)
eegt$cond_char <- as.numeric(eegt$cond_char)
eegt$speed_cond_num <- as.numeric(eegt$cond_char)
eegt <- mutate(eegt,across(c('subj_char'), factor))
eegt <- mutate(eegt,across(c('group_char'), factor))
eegt$speed_ord <- cut(eegt$cond_char, 4, ordered = TRUE)
eegt <- mutate(eegt,across(c('cond_char'), factor))
eegt$group_speed_code = paste(eegt$group_char,eegt$cond_char,sep="_")
head(eegt)

create ratios

Log <- function(x, base = exp(1)) {
  LOG <- base::log(as.complex(x), base = base)
  if (all(Im(LOG) == 0)) { LOG <- Re(LOG) }
  LOG }
#%% CALCS
eegt <- eegt%>%
  mutate(beta_div_theta=beta_avg_power/theta_avg_power)
eegt <- eegt%>%
  mutate(theta_div_beta=theta_avg_power/beta_avg_power)
eegt <- eegt%>%
  mutate(log_beta_div_theta=log10(beta_avg_power/theta_avg_power+max(abs(beta_avg_power/theta_avg_power))))
eegt <- eegt%>%
  mutate(log_theta_div_beta=log10(theta_avg_power/beta_avg_power+max(abs(theta_avg_power/beta_avg_power))))
# eegt <- eegt%>%
#   mutate(log_beta_div_theta=log10(beta_avg_power/theta_avg_power+mean(abs(beta_avg_power/theta_avg_power))/(mean(abs(beta_avg_power/theta_avg_power))+3*sd(abs(beta_avg_power/theta_avg_power)))));
# eegt <- eegt%>%
#   mutate(log_theta_div_beta=log10(theta_avg_power/beta_avg_power+mean(abs(theta_avg_power/beta_avg_power))/(mean(abs(theta_avg_power/beta_avg_power))+3*sd(abs(theta_avg_power/beta_avg_power)))));
# eegt <- eegt%>%
#   mutate(log_beta_div_theta=log10((beta_avg_power/theta_avg_power)+abs(min((beta_avg_power/theta_avg_power)))));
# eegt <- eegt%>%
#   mutate(log_theta_div_beta=log10((theta_avg_power/beta_avg_power)+abs(min((theta_avg_power/beta_avg_power)))));
eegt <- eegt%>%
  mutate(log_beta_div_theta=Re(Log((beta_avg_power/theta_avg_power),10)*Conj(Log((theta_avg_power/beta_avg_power),10))));
eegt <- eegt%>%
  mutate(log_theta_div_beta=Re(Log((theta_avg_power/beta_avg_power),10)*Conj(Log((theta_avg_power/beta_avg_power),10))));

LME EEG ~ 1+kin+group+kin:group

Changes in theta_avg_power for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -66 (-230 to 98) 0.43 0.90 0.12 (-3.3 to 3.5) 0.95 0.95 -1.0 (-2.0 to -0.09) 0.032 0.13 2.0 (0.82 to 3.1) <0.001 0.003
mean_APexc_COV 2.5 (-7.3 to 12) 0.62 0.90 0.01 (-0.20 to 0.21) 0.95 0.95 0.01 (-0.04 to 0.07) 0.65 0.87 -0.02 (-0.08 to 0.05) 0.62 0.82
group_char
0.75 0.90
0.75 0.95
0.57 0.87
0.33 0.66
    H1000’s







    H2000’s 89 (-169 to 346)

0.55 (-4.8 to 5.9)

0.58 (-0.95 to 2.1)

-0.77 (-2.6 to 1.1)

    H3000’s 71 (-149 to 292)

-1.3 (-5.8 to 3.3)

0.68 (-0.63 to 2.0)

-1.2 (-2.9 to 0.41)

mean_APexc_COV * group_char
0.90 0.90
0.64 0.95
0.96 0.96
0.97 0.97
    mean_APexc_COV * H2000’s -2.5 (-15 to 10)

-0.01 (-0.28 to 0.26)

-0.01 (-0.09 to 0.07)

0.01 (-0.08 to 0.09)

    mean_APexc_COV * H3000’s -2.6 (-14 to 8.6)

0.08 (-0.16 to 0.31)

-0.01 (-0.08 to 0.06)

0.01 (-0.07 to 0.08)

subj_char.sd__(Intercept) 34 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 206 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 128 (-16 to 271) 0.081 0.16 0.12 (-2.9 to 3.2) 0.94 0.95 -0.28 (-1.1 to 0.53) 0.49 0.66 1.0 (0.09 to 2.0) 0.033 0.13
mean_APexc_mean -2,788 (-5,298 to -277) 0.030 0.12 1.6 (-52 to 55) 0.95 0.95 -10 (-24 to 3.8) 0.15 0.62 12 (-2.3 to 26) 0.10 0.20
group_char
0.39 0.39
0.86 0.95
0.95 0.95
0.88 0.88
    H1000’s







    H2000’s -103 (-300 to 95)

-0.24 (-4.4 to 3.9)

-0.19 (-1.3 to 0.96)

-0.11 (-1.5 to 1.3)

    H3000’s -125 (-308 to 57)

0.72 (-3.1 to 4.6)

-0.06 (-1.1 to 1.0)

-0.34 (-1.7 to 0.98)

mean_APexc_mean * group_char
0.23 0.31
0.93 0.95
0.44 0.66
0.37 0.49
    mean_APexc_mean * H2000’s 2,755 (-1,085 to 6,594)

15 (-66 to 96)

12 (-9.9 to 34)

-11 (-34 to 13)

    mean_APexc_mean * H3000’s 2,780 (-816 to 6,376)

2.3 (-74 to 78)

12 (-9.1 to 32)

-16 (-39 to 7.2)

subj_char.sd__(Intercept) 26 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 206 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -150 (-278 to -22) 0.022 0.087 0.12 (-2.5 to 2.8) 0.93 0.95 -0.75 (-1.5 to 0.05) 0.066 0.27 2.2 (1.1 to 3.3) <0.001 <0.001
mean_MLexc_COV 8.7 (0.20 to 17) 0.045 0.090 0.01 (-0.17 to 0.18) 0.95 0.95 -0.01 (-0.06 to 0.05) 0.82 0.82 -0.03 (-0.10 to 0.03) 0.29 0.29
group_char
0.25 0.34
0.91 0.95
0.34 0.65
0.025 0.051
    H1000’s







    H2000’s 96 (-86 to 277)

0.66 (-3.1 to 4.4)

0.82 (-0.29 to 1.9)

-1.7 (-3.1 to -0.24)

    H3000’s 155 (-30 to 339)

-0.11 (-4.0 to 3.7)

0.31 (-0.81 to 1.4)

-1.8 (-3.3 to -0.38)

mean_MLexc_COV * group_char
0.36 0.36
0.81 0.95
0.48 0.65
0.28 0.29
    mean_MLexc_COV * H2000’s -3.4 (-15 to 8.5)

-0.02 (-0.27 to 0.23)

-0.03 (-0.10 to 0.05)

0.07 (-0.02 to 0.15)

    mean_MLexc_COV * H3000’s -8.9 (-21 to 3.4)

0.06 (-0.19 to 0.32)

0.02 (-0.06 to 0.09)

0.05 (-0.04 to 0.13)

subj_char.sd__(Intercept) 32 (NA to NA)

0.00 (NA to NA)

0.50 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 204 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 152 (30 to 274) 0.015 0.030 0.21 (-2.4 to 2.8) 0.88
0.99
-0.33 (-1.1 to 0.40) 0.38 0.50 0.80 (-0.11 to 1.7) 0.085 0.11
mean_MLexc_mean -2,174 (-3,593 to -755) 0.003 0.011 0.05 (-30 to 30)
0.99
0.99
-6.2 (-14 to 2.0) 0.14 0.41 11 (2.1 to 20) 0.015 0.061
group_char
0.18 0.18
0.96
0.99

0.69 0.69
0.70 0.70
    H1000’s







    H2000’s -94 (-256 to 69)

0.12 (-3.3 to 3.6)

-0.34 (-1.3 to 0.63)

0.39 (-0.85 to 1.6)

    H3000’s -149 (-307 to 9.0)

0.46 (-2.9 to 3.8)

0.01 (-0.94 to 0.97)

-0.09 (-1.3 to 1.1)

mean_MLexc_mean * group_char
0.050 0.067
0.98
0.99

0.21 0.41
0.042 0.083
    mean_MLexc_mean * H2000’s 1,796 (23 to 3,569)

2.9 (-35 to 41)

9.3 (-0.98 to 20)

-13 (-24 to -2.2)

    mean_MLexc_mean * H3000’s 2,162 (369 to 3,956)

3.9 (-34 to 42)

6.7 (-3.8 to 17)

-13 (-25 to -1.3)

subj_char.sd__(Intercept) 22 (NA to NA)

0.00 (NA to NA)

0.50 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 204 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 0.02 (-117 to 117)
0.99
0.99
0.24 (-2.2 to 2.7) 0.85
0.99
-0.41 (-1.1 to 0.24) 0.22 0.42 1.3 (0.54 to 2.2) 0.001 0.004
mean_StepDur -28 (-148 to 92) 0.65
0.99
-0.03 (-2.6 to 2.5) 0.98
0.99
-0.46 (-1.1 to 0.19) 0.16 0.42 0.39 (-0.27 to 1.0) 0.25 0.50
group_char
0.67
0.99

0.89
0.99

0.74 0.74
0.72 0.72
    H1000’s







    H2000’s 85 (-112 to 281)

0.30 (-3.8 to 4.4)

-0.35 (-1.5 to 0.75)

-0.12 (-1.4 to 1.2)

    H3000’s 2.4 (-187 to 192)

0.95 (-3.0 to 4.9)

0.11 (-0.97 to 1.2)

-0.54 (-1.8 to 0.77)

mean_StepDur * group_char
0.85
0.99

0.99
0.99

0.31 0.42
0.41 0.55
    mean_StepDur * H2000’s -53 (-287 to 181)

0.12 (-4.8 to 5.1)

0.96 (-0.32 to 2.2)

-0.71 (-2.0 to 0.61)

    mean_StepDur * H3000’s 27 (-214 to 268)

-0.24 (-5.3 to 4.8)

0.50 (-0.85 to 1.9)

-0.76 (-2.2 to 0.68)

subj_char.sd__(Intercept) 33 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 206 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -21 (-119 to 76) 0.67 0.93 0.19 (-1.8 to 2.2) 0.85 0.99 -0.74 (-1.3 to -0.18) 0.010 0.040 1.4 (0.71 to 2.2) <0.001 <0.001
mean_UDexc_COV -0.33 (-7.3 to 6.7) 0.93 0.93 0.00 (-0.15 to 0.15) 0.99 0.99 -0.01 (-0.05 to 0.03) 0.69 0.69 0.02 (-0.02 to 0.06) 0.34 0.50
group_char
0.40 0.93
0.58 0.99
0.44 0.59
0.56 0.56
    H1000’s







    H2000’s 102 (-48 to 251)

0.20 (-2.9 to 3.3)

-0.08 (-0.94 to 0.78)

-0.27 (-1.4 to 0.85)

    H3000’s 25 (-128 to 177)

-1.4 (-4.6 to 1.7)

0.48 (-0.40 to 1.4)

-0.62 (-1.7 to 0.51)

mean_UDexc_COV * group_char
0.70 0.93
0.32 0.99
0.37 0.59
0.37 0.50
    mean_UDexc_COV * H2000’s -3.8 (-14 to 6.5)

0.01 (-0.20 to 0.23)

0.04 (-0.02 to 0.10)

-0.03 (-0.09 to 0.03)

    mean_UDexc_COV * H3000’s 0.23 (-10 to 11)

0.16 (-0.06 to 0.38)

0.01 (-0.05 to 0.07)

-0.04 (-0.10 to 0.02)

subj_char.sd__(Intercept) 33 (NA to NA)

0.00 (NA to NA)

0.48 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 206 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -1.6 (-114 to 111) 0.98 0.98 0.14 (-2.2 to 2.5) 0.91 0.95 -0.97 (-1.6 to -0.32) 0.003 0.013 2.3 (1.5 to 3.1) <0.001 <0.001
mean_UDexc_mean -1,008 (-5,440 to 3,424) 0.66 0.98 2.8 (-91 to 97) 0.95 0.95 5.5 (-19 to 30) 0.66 0.66 -24 (-49 to 1.6) 0.067 0.067
group_char
0.80 0.98
0.63 0.95
0.057 0.11
0.002 0.003
    H1000’s







    H2000’s -46 (-208 to 116)

0.00 (-3.4 to 3.4)

1.1 (0.21 to 2.1)

-1.7 (-2.9 to -0.50)

    H3000’s 4.9 (-153 to 162)

1.4 (-1.9 to 4.7)

0.54 (-0.37 to 1.5)

-2.0 (-3.1 to -0.81)

mean_UDexc_mean * group_char
0.44 0.98
0.82 0.95
0.16 0.22
0.062 0.067
    mean_UDexc_mean * H2000’s 3,946 (-2,338 to 10,231)

16 (-116 to 149)

-29 (-64 to 6.0)

40 (4.2 to 77)

    mean_UDexc_mean * H3000’s 953 (-5,165 to 7,072)

-25 (-154 to 104)

0.75 (-34 to 35)

34 (-2.2 to 71)

subj_char.sd__(Intercept) 36 (NA to NA)

0.00 (NA to NA)

0.50 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 205 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -8.9 (-107 to 89) 0.86 0.86 0.22 (-1.8 to 2.3) 0.83 0.99 -0.49 (-1.0 to 0.07) 0.087 0.31 1.4 (0.71 to 2.2) <0.001 <0.001
mean_StanceDur -13 (-85 to 58) 0.72 0.86 -0.01 (-1.5 to 1.5) 0.99 0.99 -0.28 (-0.67 to 0.11) 0.15 0.31 0.21 (-0.18 to 0.61) 0.29 0.52
group_char
0.59 0.86
0.84 0.99
0.74 0.74
0.52 0.52
    H1000’s







    H2000’s 82 (-80 to 245)

0.62 (-2.8 to 4.0)

-0.23 (-1.2 to 0.69)

-0.24 (-1.4 to 0.92)

    H3000’s 11 (-148 to 171)

0.97 (-2.4 to 4.3)

0.17 (-0.74 to 1.1)

-0.67 (-1.8 to 0.48)

mean_StanceDur * group_char
0.84 0.86
0.98 0.99
0.27 0.37
0.41 0.52
    mean_StanceDur * H2000’s -35 (-174 to 103)

-0.23 (-3.2 to 2.7)

0.60 (-0.16 to 1.4)

-0.42 (-1.2 to 0.36)

    mean_StanceDur * H3000’s 13 (-134 to 160)

-0.20 (-3.3 to 2.9)

0.32 (-0.49 to 1.1)

-0.45 (-1.3 to 0.40)

subj_char.sd__(Intercept) 32 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 206 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 0.06 (-117 to 117)
0.99
0.99
0.24 (-2.2 to 2.7) 0.85
0.99
-0.41 (-1.1 to 0.24) 0.22 0.42 1.3 (0.54 to 2.2) 0.001 0.004
mean_GaitCycleDur -14 (-74 to 46) 0.65
0.99
-0.01 (-1.3 to 1.3) 0.98
0.99
-0.23 (-0.56 to 0.09) 0.16 0.42 0.19 (-0.14 to 0.52) 0.25 0.50
group_char
0.67
0.99

0.89
0.99

0.74 0.74
0.71 0.71
    H1000’s







    H2000’s 84 (-112 to 281)

0.29 (-3.8 to 4.4)

-0.35 (-1.5 to 0.75)

-0.13 (-1.4 to 1.2)

    H3000’s 2.4 (-187 to 192)

0.97 (-3.0 to 4.9)

0.11 (-0.97 to 1.2)

-0.54 (-1.8 to 0.77)

mean_GaitCycleDur * group_char
0.85
0.99

0.99
0.99

0.32 0.42
0.41 0.55
    mean_GaitCycleDur * H2000’s -26 (-143 to 90)

0.06 (-2.4 to 2.5)

0.48 (-0.16 to 1.1)

-0.35 (-1.0 to 0.31)

    mean_GaitCycleDur * H3000’s 14 (-107 to 134)

-0.13 (-2.7 to 2.4)

0.25 (-0.43 to 0.93)

-0.38 (-1.1 to 0.34)

subj_char.sd__(Intercept) 33 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 206 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 3
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -53 (-146 to 39) 0.26 0.70 0.16 (-1.8 to 2.1) 0.88 0.97 -1.0 (-1.5 to -0.47) <0.001 <0.001 2.1 (1.4 to 2.8) <0.001 <0.001
mean_PeakUpDownVel_mean 119 (-235 to 473) 0.51 0.70 0.24 (-7.3 to 7.8) 0.95 0.97 0.70 (-1.2 to 2.6) 0.48 0.48 -1.9 (-3.8 to 0.10) 0.063 0.065
group_char
0.70 0.70
0.73 0.97
0.029 0.058
0.001 0.002
    H1000’s







    H2000’s 20 (-116 to 157)

0.64 (-2.2 to 3.5)

1.1 (0.27 to 1.8)

-1.4 (-2.5 to -0.40)

    H3000’s 56 (-75 to 188)

1.1 (-1.6 to 3.9)

0.63 (-0.13 to 1.4)

-1.8 (-2.8 to -0.78)

mean_PeakUpDownVel_mean * group_char
0.65 0.70
0.97 0.97
0.16 0.21
0.065 0.065
    mean_PeakUpDownVel_mean * H2000’s 100 (-394 to 593)

-0.99 (-11 to 9.5)

-2.4 (-5.1 to 0.29)

3.0 (0.25 to 5.7)

    mean_PeakUpDownVel_mean * H3000’s -123 (-599 to 353)

-1.3 (-11 to 8.8)

-0.33 (-3.0 to 2.3)

2.7 (-0.07 to 5.4)

subj_char.sd__(Intercept) 36 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 205 (NA to NA)

4.4 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.4 (-286 to 293) 0.98 0.98 -0.04 (-1.1 to 1.0) 0.94 0.94 -0.68 (-2.0 to 0.61) 0.30
0.99
1.0 (-0.28 to 2.3) 0.13 0.42
mean_APexc_COV 0.32 (-17 to 18) 0.97 0.98 0.03 (-0.04 to 0.09) 0.38 0.84 0.01 (-0.07 to 0.08) 0.85
0.99
0.02 (-0.05 to 0.10) 0.55 0.55
group_char
0.47 0.98
0.65 0.87
0.99
0.99

0.21 0.42
    H1000’s







    H2000’s -2.0 (-487 to 483)

-0.08 (-1.8 to 1.7)

-0.03 (-2.2 to 2.2)

1.9 (-0.28 to 4.0)

    H3000’s 219 (-174 to 612)

0.57 (-0.84 to 2.0)

0.04 (-1.8 to 1.9)

1.1 (-0.78 to 2.9)

mean_APexc_COV * group_char
0.73 0.98
0.42 0.84
0.99
0.99

0.55 0.55
    mean_APexc_COV * H2000’s -0.05 (-25 to 25)

-0.01 (-0.10 to 0.08)

0.01 (-0.10 to 0.11)

-0.05 (-0.15 to 0.05)

    mean_APexc_COV * H3000’s -6.6 (-27 to 14)

-0.04 (-0.12 to 0.03)

0.00 (-0.09 to 0.09)

-0.01 (-0.09 to 0.08)

subj_char.sd__(Intercept) 15 (NA to NA)

0.16 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 353 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.6 (-243 to 249) 0.98 0.98 0.22 (-0.66 to 1.1) 0.63 0.86 -0.41 (-1.4 to 0.62) 0.44 0.89 1.0 (0.00 to 2.0) 0.049 0.20
mean_APexc_mean 106 (-4,202 to 4,415) 0.96 0.98 3.6 (-12 to 19) 0.64 0.86 -2.9 (-19 to 14) 0.73 0.89 6.0 (-9.8 to 22) 0.46 0.53
group_char
0.79 0.98
0.91 0.91
0.89 0.89
0.15 0.30
    H1000’s







    H2000’s 32 (-311 to 375)

0.20 (-1.0 to 1.4)

-0.16 (-1.7 to 1.3)

1.4 (-0.05 to 2.9)

    H3000’s -77 (-403 to 249)

0.25 (-0.91 to 1.4)

0.22 (-1.3 to 1.7)

1.0 (-0.47 to 2.5)

mean_APexc_mean * group_char
0.48 0.98
0.61 0.86
0.80 0.89
0.53 0.53
    mean_APexc_mean * H2000’s -708 (-7,271 to 5,856)

-7.3 (-31 to 16)

6.7 (-19 to 33)

-11 (-36 to 15)

    mean_APexc_mean * H3000’s 3,333 (-3,253 to 9,920)

-12 (-35 to 12)

-3.3 (-31 to 25)

5.7 (-21 to 33)

subj_char.sd__(Intercept) 45 (NA to NA)

0.17 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 350 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 22 (-177 to 221) 0.83 0.89 -0.05 (-0.77 to 0.66) 0.88 0.88 -0.84 (-1.9 to 0.21) 0.12 0.47 2.2 (1.1 to 3.2) <0.001 <0.001
mean_MLexc_COV -0.92 (-14 to 12) 0.89 0.89 0.03 (-0.01 to 0.08) 0.17 0.65 0.02 (-0.04 to 0.08) 0.56 0.56 -0.06 (-0.12 to 0.01) 0.082 0.16
group_char
0.080 0.29
0.48 0.65
0.49 0.56
0.31 0.31
    H1000’s







    H2000’s -46 (-354 to 261)

0.53 (-0.57 to 1.6)

0.71 (-0.83 to 2.2)

-0.20 (-1.7 to 1.3)

    H3000’s 302 (-8.3 to 612)

-0.16 (-1.3 to 0.95)

-0.20 (-1.7 to 1.3)

0.94 (-0.59 to 2.5)

mean_MLexc_COV * group_char
0.14 0.29
0.41 0.65
0.45 0.56
0.23 0.30
    mean_MLexc_COV * H2000’s 3.2 (-17 to 24)

-0.05 (-0.12 to 0.03)

-0.04 (-0.13 to 0.06)

0.08 (-0.02 to 0.17)

    mean_MLexc_COV * H3000’s -18 (-38 to 2.9)

-0.01 (-0.08 to 0.07)

0.02 (-0.07 to 0.12)

0.01 (-0.08 to 0.10)

subj_char.sd__(Intercept) 11 (NA to NA)

0.12 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 351 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -1.9 (-214 to 210) 0.99 0.99 0.25 (-0.51 to 1.0) 0.51 0.89 -0.44 (-1.4 to 0.54) 0.38 0.51 0.79 (-0.19 to 1.8) 0.11 0.15
mean_MLexc_mean 129 (-2,369 to 2,626) 0.92 0.99 2.0 (-7.0 to 11) 0.66 0.89 -1.6 (-12 to 8.9) 0.76 0.76 7.0 (-3.1 to 17) 0.17 0.17
group_char
0.34 0.68
0.94 0.94
0.23 0.47
0.039 0.15
    H1000’s







    H2000’s 35 (-259 to 330)

0.06 (-1.0 to 1.1)

-0.36 (-1.7 to 1.0)

1.8 (0.42 to 3.2)

    H3000’s -157 (-439 to 125)

0.17 (-0.84 to 1.2)

0.75 (-0.58 to 2.1)

0.95 (-0.40 to 2.3)

mean_MLexc_mean * group_char
0.10 0.42
0.66 0.89
0.094 0.38
0.077 0.15
    mean_MLexc_mean * H2000’s -412 (-3,642 to 2,817)

-2.7 (-14 to 9.0)

5.9 (-7.4 to 19)

-11 (-23 to 2.3)

    mean_MLexc_mean * H3000’s 2,531 (-688 to 5,749)

-5.3 (-17 to 6.2)

-7.4 (-21 to 6.2)

2.0 (-11 to 15)

subj_char.sd__(Intercept) 58 (NA to NA)

0.18 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 345 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.6 (-196 to 201) 0.98 0.98 0.57 (-0.15 to 1.3) 0.12 0.49 -0.34 (-1.2 to 0.50) 0.43 0.51 1.2 (0.39 to 2.1) 0.004 0.016
mean_StepDur 6.4 (-198 to 210) 0.95 0.98 -0.17 (-0.91 to 0.57) 0.65 0.96 -0.25 (-0.99 to 0.49) 0.51 0.51 0.13 (-0.58 to 0.83) 0.73 0.73
group_char
0.037 0.073
0.96 0.96
0.15 0.31
0.17 0.22
    H1000’s







    H2000’s 27 (-321 to 376)

-0.17 (-1.4 to 1.1)

-0.24 (-1.7 to 1.2)

1.2 (-0.21 to 2.7)

    H3000’s -405 (-741 to -69)

-0.12 (-1.3 to 1.1)

1.2 (-0.20 to 2.7)

-0.18 (-1.6 to 1.3)

mean_StepDur * group_char
0.006 0.025
0.94 0.96
0.086 0.31
0.036 0.071
    mean_StepDur * H2000’s -36 (-448 to 376)

-0.02 (-1.5 to 1.5)

0.48 (-1.1 to 2.0)

-0.41 (-1.9 to 1.1)

    mean_StepDur * H3000’s 675 (242 to 1,108)

-0.28 (-1.9 to 1.3)

-1.7 (-3.4 to 0.01)

2.0 (0.33 to 3.6)

subj_char.sd__(Intercept) 26 (NA to NA)

0.14 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 345 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 9.2 (-158 to 176) 0.91
0.99
0.57 (-0.03 to 1.2) 0.063 0.25 -0.60 (-1.4 to 0.16) 0.12 0.16 1.1 (0.34 to 1.9) 0.005 0.012
mean_UDexc_COV -0.06 (-12 to 12)
0.99
0.99
-0.01 (-0.06 to 0.03) 0.58 0.85 0.00 (-0.04 to 0.05) 0.90 0.90 0.02 (-0.02 to 0.06) 0.37 0.37
group_char
0.20 0.40
0.85 0.85
0.092 0.16
0.056 0.075
    H1000’s







    H2000’s 8.1 (-246 to 263)

-0.26 (-1.2 to 0.66)

0.04 (-1.1 to 1.2)

1.3 (0.11 to 2.5)

    H3000’s -221 (-491 to 48)

-0.07 (-1.0 to 0.90)

1.2 (0.04 to 2.5)

-0.05 (-1.3 to 1.2)

mean_UDexc_COV * group_char
0.062 0.25
0.84 0.85
0.037 0.15
0.006 0.012
    mean_UDexc_COV * H2000’s -0.69 (-19 to 17)

0.01 (-0.06 to 0.07)

0.01 (-0.06 to 0.08)

-0.03 (-0.09 to 0.03)

    mean_UDexc_COV * H3000’s 20 (1.2 to 38)

-0.01 (-0.08 to 0.05)

-0.08 (-0.15 to -0.01)

0.08 (0.02 to 0.15)

subj_char.sd__(Intercept) 40 (NA to NA)

0.13 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 347 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.7 (-198 to 203) 0.98 0.98 0.38 (-0.34 to 1.1) 0.30 0.71 -0.80 (-1.7 to 0.06) 0.068 0.27 2.0 (1.1 to 2.8) <0.001 <0.001
mean_UDexc_mean 240 (-7,586 to 8,066) 0.95 0.98 1.4 (-27 to 29) 0.92 0.92 10 (-20 to 39) 0.51 0.51 -26 (-54 to 2.0) 0.069 0.069
group_char
0.086 0.32
0.35 0.71
0.30 0.40
0.015 0.031
    H1000’s







    H2000’s 6.5 (-291 to 304)

-0.70 (-1.8 to 0.37)

0.45 (-0.84 to 1.7)

0.36 (-0.94 to 1.6)

    H3000’s 282 (0.57 to 563)

-0.61 (-1.6 to 0.39)

-0.58 (-1.8 to 0.67)

1.8 (0.52 to 3.0)

mean_UDexc_mean * group_char
0.16 0.32
0.58 0.77
0.16 0.31
0.068 0.069
    mean_UDexc_mean * H2000’s -314 (-11,625 to 10,997)

21 (-19 to 62)

-12 (-54 to 31)

23 (-17 to 64)

    mean_UDexc_mean * H3000’s -9,439 (-20,380 to 1,502)

14 (-25 to 53)

29 (-13 to 72)

-26 (-66 to 15)

subj_char.sd__(Intercept) 42 (NA to NA)

0.09 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 348 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.7 (-164 to 169) 0.98 0.98 0.56 (-0.04 to 1.2) 0.069 0.28 -0.36 (-1.1 to 0.38) 0.34 0.46 1.3 (0.50 to 2.0) 0.001 0.004
mean_StanceDur 4.6 (-117 to 126) 0.94 0.98 -0.12 (-0.56 to 0.32) 0.61 0.92 -0.16 (-0.60 to 0.27) 0.46 0.46 0.08 (-0.34 to 0.50) 0.72 0.72
group_char
0.071 0.14
0.90 0.92
0.24 0.46
0.13 0.18
    H1000’s







    H2000’s 17 (-270 to 303)

-0.23 (-1.3 to 0.81)

-0.14 (-1.4 to 1.1)

1.2 (-0.03 to 2.5)

    H3000’s -307 (-591 to -24)

-0.14 (-1.2 to 0.89)

0.94 (-0.29 to 2.2)

0.07 (-1.2 to 1.3)

mean_StanceDur * group_char
0.011 0.042
0.92 0.92
0.12 0.46
0.028 0.056
    mean_StanceDur * H2000’s -16 (-259 to 227)

0.04 (-0.84 to 0.92)

0.26 (-0.64 to 1.2)

-0.29 (-1.1 to 0.57)

    mean_StanceDur * H3000’s 393 (128 to 659)

-0.18 (-1.1 to 0.78)

-0.93 (-1.9 to 0.08)

1.2 (0.22 to 2.1)

subj_char.sd__(Intercept) 28 (NA to NA)

0.14 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 346 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.6 (-195 to 201) 0.98 0.98 0.57 (-0.15 to 1.3) 0.12 0.48 -0.34 (-1.2 to 0.50) 0.43 0.51 1.2 (0.39 to 2.1) 0.004 0.016
mean_GaitCycleDur 3.2 (-99 to 105) 0.95 0.98 -0.09 (-0.46 to 0.28) 0.65 0.96 -0.12 (-0.49 to 0.25) 0.51 0.51 0.06 (-0.29 to 0.42) 0.73 0.73
group_char
0.036 0.072
0.96 0.96
0.15 0.31
0.17 0.22
    H1000’s







    H2000’s 27 (-320 to 375)

-0.17 (-1.4 to 1.1)

-0.24 (-1.7 to 1.2)

1.2 (-0.20 to 2.7)

    H3000’s -406 (-742 to -70)

-0.12 (-1.3 to 1.1)

1.2 (-0.20 to 2.7)

-0.18 (-1.6 to 1.3)

mean_GaitCycleDur * group_char
0.006 0.024
0.94 0.96
0.085 0.31
0.035 0.070
    mean_GaitCycleDur * H2000’s -18 (-223 to 187)

-0.01 (-0.76 to 0.73)

0.24 (-0.53 to 1.0)

-0.21 (-0.94 to 0.53)

    mean_GaitCycleDur * H3000’s 338 (121 to 554)

-0.14 (-0.93 to 0.65)

-0.85 (-1.7 to 0.00)

0.98 (0.17 to 1.8)

subj_char.sd__(Intercept) 25 (NA to NA)

0.14 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 345 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 4
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.8 (-155 to 169) 0.93 0.98 0.36 (-0.22 to 0.94) 0.23 0.73 -0.72 (-1.4 to 0.00) 0.050 0.20 1.7 (1.0 to 2.5) <0.001 <0.001
mean_PeakUpDownVel_mean 7.0 (-608 to 622) 0.98 0.98 0.25 (-2.0 to 2.5) 0.83 0.83 0.66 (-1.6 to 2.9) 0.56 0.56 -1.7 (-3.8 to 0.44) 0.12 0.12
group_char
0.083 0.33
0.37 0.73
0.40 0.53
0.007 0.014
    H1000’s







    H2000’s -13 (-259 to 234)

-0.54 (-1.4 to 0.34)

0.41 (-0.70 to 1.5)

0.49 (-0.63 to 1.6)

    H3000’s 230 (-3.0 to 462)

-0.52 (-1.4 to 0.31)

-0.38 (-1.5 to 0.69)

1.7 (0.62 to 2.8)

mean_PeakUpDownVel_mean * group_char
0.18 0.36
0.67 0.83
0.20 0.41
0.060 0.080
    mean_PeakUpDownVel_mean * H2000’s 43 (-847 to 934)

1.4 (-1.8 to 4.6)

-1.0 (-4.2 to 2.2)

1.8 (-1.3 to 4.8)

    mean_PeakUpDownVel_mean * H3000’s -670 (-1,514 to 174)

0.94 (-2.1 to 4.0)

1.9 (-1.3 to 5.1)

-2.0 (-5.0 to 1.0)

subj_char.sd__(Intercept) 32 (NA to NA)

0.09 (NA to NA)

1.1 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 350 (NA to NA)

1.3 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.7 (-459 to 462)
0.99
0.99
0.12 (-14 to 14) 0.99 0.99 -0.79 (-2.2 to 0.63) 0.27 0.27 1.7 (0.28 to 3.1) 0.019 0.026
mean_APexc_COV -0.11 (-27 to 27)
0.99
0.99
0.02 (-0.82 to 0.86) 0.96 0.99 0.05 (-0.04 to 0.13) 0.27 0.27 -0.02 (-0.10 to 0.06) 0.65 0.65
group_char
<0.001 <0.001
0.79 0.99
<0.001 <0.001
<0.001 <0.001
    H1000’s







    H2000’s -4,333 (-5,151 to -3,516)

4.8 (-19 to 29)

7.4 (4.9 to 9.9)

-6.7 (-9.2 to -4.1)

    H3000’s 1.0 (-721 to 723)

7.1 (-13 to 27)

1.1 (-1.1 to 3.3)

-0.94 (-3.2 to 1.3)

mean_APexc_COV * group_char
<0.001 <0.001
0.89 0.99
<0.001 <0.001
<0.001 <0.001
    mean_APexc_COV * H2000’s 211 (172 to 250)

-0.29 (-1.5 to 0.91)

-0.40 (-0.52 to -0.28)

0.37 (0.25 to 0.49)

    mean_APexc_COV * H3000’s -0.04 (-33 to 33)

-0.16 (-1.2 to 0.84)

-0.06 (-0.16 to 0.05)

0.05 (-0.05 to 0.15)

subj_char.sd__(Intercept) 368 (NA to NA)

3.5 (NA to NA)

0.99 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 390 (NA to NA)

14 (NA to NA)

1.2 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -12 (-485 to 461) 0.96
0.99
-0.22 (-11 to 10) 0.97 0.97 -0.47 (-1.7 to 0.73) 0.44 0.80 1.5 (0.27 to 2.7) 0.017 0.068
mean_APexc_mean 223 (-8,190 to 8,637) 0.96
0.99
12 (-175 to 200) 0.90 0.97 8.1 (-13 to 29) 0.45 0.80 -1.8 (-22 to 19) 0.87 0.87
group_char
0.82
0.99

0.025 0.10
0.60 0.80
0.81 0.87
    H1000’s







    H2000’s 254 (-577 to 1,085)

-17 (-36 to 1.8)

-0.88 (-3.0 to 1.3)

-0.01 (-2.2 to 2.2)

    H3000’s 18 (-633 to 668)

9.1 (-5.9 to 24)

0.22 (-1.5 to 1.9)

-0.58 (-2.4 to 1.3)

mean_APexc_mean * group_char
0.99
0.99

0.057 0.11
0.99
0.99

0.34 0.67
    mean_APexc_mean * H2000’s 94 (-15,874 to 16,063)

328 (-30 to 687)

-1.5 (-42 to 39)

27 (-13 to 66)

    mean_APexc_mean * H3000’s -399 (-14,034 to 13,236)

-152 (-466 to 162)

0.75 (-35 to 37)

19 (-18 to 56)

subj_char.sd__(Intercept) 0.00 (NA to NA)

4.1 (NA to NA)

0.61 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 639 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 4.5 (-343 to 352) 0.98 0.98 -0.55 (-9.2 to 8.1) 0.90 0.90 -0.22 (-1.2 to 0.80) 0.68 0.90 2.0 (0.93 to 3.2) <0.001 0.001
mean_MLexc_COV -0.30 (-22 to 22) 0.98 0.98 0.07 (-0.47 to 0.61) 0.81 0.90 0.01 (-0.05 to 0.07) 0.71 0.90 -0.04 (-0.11 to 0.02) 0.20 0.20
group_char
0.014 0.028
0.38 0.76
0.90 0.90
0.12 0.16
    H1000’s







    H2000’s -1,170 (-1,973 to -366)

11 (-8.5 to 31)

0.51 (-1.7 to 2.8)

-1.4 (-3.8 to 0.95)

    H3000’s -1.0 (-681 to 679)

-4.7 (-21 to 12)

0.06 (-1.8 to 1.9)

-2.0 (-3.9 to 0.00)

mean_MLexc_COV * group_char
<0.001 0.003
0.18 0.71
0.34 0.90
0.009 0.018
    mean_MLexc_COV * H2000’s 102 (48 to 157)

-0.89 (-2.2 to 0.42)

-0.11 (-0.26 to 0.04)

0.19 (0.04 to 0.34)

    mean_MLexc_COV * H3000’s -0.02 (-45 to 45)

0.55 (-0.54 to 1.6)

0.00 (-0.12 to 0.13)

0.15 (0.03 to 0.27)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.7 (NA to NA)

0.62 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 612 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -16 (-407 to 374) 0.93 0.93 0.48 (-8.6 to 9.6) 0.92
0.99
-0.01 (-1.1 to 1.0)
0.99
0.99
1.1 (-0.01 to 2.2) 0.051 0.20
mean_MLexc_mean 207 (-4,438 to 4,851) 0.93 0.93 -0.31 (-107 to 107)
0.99
0.99
-0.41 (-13 to 12) 0.95
0.99
3.5 (-8.9 to 16) 0.58 0.61
group_char
0.32 0.93
0.019 0.077
0.40
0.99

0.54 0.61
    H1000’s







    H2000’s 505 (-201 to 1,210)

-16 (-33 to -0.03)

-1.2 (-3.0 to 0.70)

1.0 (-0.96 to 3.0)

    H3000’s 16 (-536 to 567)

7.1 (-5.9 to 20)

0.05 (-1.4 to 1.5)

0.70 (-0.94 to 2.3)

mean_MLexc_mean * group_char
0.74 0.93
0.040 0.081
0.99
0.99

0.61 0.61
    mean_MLexc_mean * H2000’s -2,758 (-10,355 to 4,840)

163 (-8.2 to 335)

1.7 (-18 to 21)

2.4 (-17 to 22)

    mean_MLexc_mean * H3000’s -215 (-6,420 to 5,990)

-48 (-191 to 96)

0.81 (-16 to 17)

-6.3 (-23 to 11)

subj_char.sd__(Intercept) 0.00 (NA to NA)

4.7 (NA to NA)

0.60 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 638 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.4 (-396 to 383) 0.97 0.97 -0.07 (-8.7 to 8.6) 0.99 0.99 -0.41 (-1.4 to 0.57) 0.41 0.83 1.3 (0.30 to 2.3) 0.011 0.043
mean_StepDur 7.1 (-402 to 416) 0.97 0.97 0.59 (-8.3 to 9.5) 0.90 0.99 0.42 (-0.58 to 1.4) 0.41 0.83 0.10 (-0.84 to 1.0) 0.83 0.97
group_char
0.23 0.93
0.014 0.050
0.75 0.98
0.97 0.97
    H1000’s







    H2000’s 749 (-132 to 1,630)

-24 (-44 to -4.5)

-0.77 (-3.0 to 1.4)

0.27 (-2.0 to 2.5)

    H3000’s 14 (-716 to 745)

8.9 (-7.7 to 26)

0.16 (-1.8 to 2.1)

-0.06 (-2.0 to 1.9)

mean_StepDur * group_char
0.50 0.97
0.025 0.050
0.98 0.98
0.57 0.97
    mean_StepDur * H2000’s -627 (-1,678 to 424)

29 (5.9 to 52)

-0.24 (-2.8 to 2.3)

1.3 (-1.1 to 3.7)

    mean_StepDur * H3000’s -21 (-1,006 to 964)

-8.6 (-31 to 14)

0.09 (-2.4 to 2.6)

0.41 (-2.1 to 2.9)

subj_char.sd__(Intercept) 0.00 (NA to NA)

4.2 (NA to NA)

0.60 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 636 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -5.7 (-324 to 313) 0.97 0.97 -0.36 (-7.7 to 7.0) 0.92 0.92 -0.43 (-1.3 to 0.40) 0.30 0.46 1.4 (0.52 to 2.3) 0.002 0.007
mean_UDexc_COV 0.44 (-22 to 23) 0.97 0.97 0.06 (-0.45 to 0.58) 0.81 0.92 0.03 (-0.03 to 0.09) 0.29 0.46 0.00 (-0.05 to 0.05) 0.99 0.99
group_char
0.81 0.97
0.13 0.52
0.75 0.75
0.96 0.99
    H1000’s







    H2000’s -195 (-810 to 421)

-9.3 (-24 to 4.9)

0.03 (-1.6 to 1.6)

-0.22 (-1.9 to 1.5)

    H3000’s 8.1 (-579 to 595)

7.7 (-5.8 to 21)

0.56 (-0.95 to 2.1)

0.06 (-1.5 to 1.6)

mean_UDexc_COV * group_char
0.26 0.97
0.26 0.52
0.35 0.46
0.089 0.18
    mean_UDexc_COV * H2000’s 32 (-8.8 to 74)

0.56 (-0.38 to 1.5)

-0.08 (-0.18 to 0.03)

0.11 (0.01 to 0.21)

    mean_UDexc_COV * H3000’s -0.69 (-40 to 39)

-0.33 (-1.2 to 0.56)

-0.03 (-0.13 to 0.06)

0.01 (-0.08 to 0.10)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.5 (NA to NA)

0.59 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 633 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 7.6 (-362 to 377) 0.97 0.97 0.60 (-7.8 to 9.0) 0.89 0.97 0.26 (-0.70 to 1.2) 0.60 0.60 1.3 (0.28 to 2.3) 0.012 0.033
mean_UDexc_mean -316 (-14,912 to 14,279) 0.97 0.97 -6.0 (-333 to 321) 0.97 0.97 -12 (-49 to 24) 0.51 0.60 5.3 (-30 to 41) 0.77 0.77
group_char
0.062 0.25
0.14 0.27
0.045 0.18
0.016 0.033
    H1000’s







    H2000’s 846 (100 to 1,593)

16 (-0.82 to 33)

-2.4 (-4.4 to -0.49)

2.8 (0.79 to 4.8)

    H3000’s -11 (-580 to 558)

-0.57 (-14 to 12)

-0.32 (-1.8 to 1.2)

0.01 (-1.6 to 1.6)

mean_UDexc_mean * group_char
0.22 0.43
0.035 0.14
0.29 0.57
0.15 0.20
    mean_UDexc_mean * H2000’s -24,211 (-53,231 to 4,808)

-727 (-1,380 to -73)

59 (-14 to 132)

-64 (-135 to 7.7)

    mean_UDexc_mean * H3000’s 411 (-21,507 to 22,329)

149 (-346 to 644)

19 (-37 to 74)

7.1 (-47 to 61)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.7 (NA to NA)

0.60 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 633 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -4.6 (-333 to 324) 0.98 0.98 0.03 (-7.3 to 7.3)
0.99
0.99
-0.38 (-1.2 to 0.46) 0.38 0.75 1.3 (0.44 to 2.2) 0.003 0.013
mean_StanceDur 3.8 (-244 to 251) 0.98 0.98 0.35 (-5.0 to 5.7) 0.90
0.99
0.28 (-0.33 to 0.88) 0.37 0.75 0.07 (-0.50 to 0.64) 0.82 0.85
group_char
0.26 0.98
0.012 0.044
0.68 0.91
0.85 0.85
    H1000’s







    H2000’s 579 (-127 to 1,285)

-19 (-35 to -3.4)

-0.68 (-2.5 to 1.1)

0.52 (-1.3 to 2.4)

    H3000’s 10 (-600 to 621)

8.0 (-5.8 to 22)

0.22 (-1.4 to 1.8)

0.00 (-1.7 to 1.7)

mean_StanceDur * group_char
0.61 0.98
0.022 0.044
0.94 0.94
0.60 0.85
    mean_StanceDur * H2000’s -299 (-896 to 299)

16 (3.5 to 29)

-0.27 (-1.7 to 1.2)

0.71 (-0.67 to 2.1)

    mean_StanceDur * H3000’s -12 (-602 to 579)

-5.3 (-18 to 7.9)

-0.01 (-1.5 to 1.5)

0.23 (-1.2 to 1.7)

subj_char.sd__(Intercept) 0.00 (NA to NA)

4.2 (NA to NA)

0.60 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 637 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.4 (-396 to 383) 0.97 0.97 -0.08 (-8.7 to 8.6) 0.99 0.99 -0.41 (-1.4 to 0.57) 0.41 0.83 1.3 (0.30 to 2.3) 0.011 0.043
mean_GaitCycleDur 3.6 (-201 to 208) 0.97 0.97 0.30 (-4.2 to 4.7) 0.90 0.99 0.21 (-0.29 to 0.71) 0.42 0.83 0.05 (-0.42 to 0.52) 0.83 0.97
group_char
0.24 0.95
0.014 0.050
0.75 0.98
0.97 0.97
    H1000’s







    H2000’s 743 (-137 to 1,623)

-24 (-43 to -4.4)

-0.77 (-3.0 to 1.4)

0.25 (-2.0 to 2.5)

    H3000’s 14 (-716 to 745)

8.9 (-7.7 to 26)

0.16 (-1.7 to 2.1)

-0.06 (-2.0 to 1.9)

mean_GaitCycleDur * group_char
0.51 0.97
0.025 0.050
0.98 0.98
0.56 0.97
    mean_GaitCycleDur * H2000’s -309 (-834 to 215)

14 (2.9 to 26)

-0.12 (-1.4 to 1.2)

0.66 (-0.56 to 1.9)

    mean_GaitCycleDur * H3000’s -11 (-503 to 482)

-4.3 (-15 to 6.8)

0.05 (-1.2 to 1.3)

0.20 (-1.1 to 1.5)

subj_char.sd__(Intercept) 0.00 (NA to NA)

4.2 (NA to NA)

0.60 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 636 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 5
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 8.3 (-297 to 313) 0.96 0.96 0.73 (-6.1 to 7.6) 0.84 0.93 0.16 (-0.62 to 0.95) 0.68 0.68 1.4 (0.62 to 2.3) <0.001 0.002
mean_PeakUpDownVel_mean -35 (-1,205 to 1,135) 0.95 0.96 -1.2 (-27 to 25) 0.93 0.93 -0.85 (-3.7 to 2.0) 0.56 0.68 -0.22 (-2.9 to 2.5) 0.87 0.87
group_char
0.18 0.74
0.18 0.35
0.076 0.30
0.021 0.041
    H1000’s







    H2000’s 553 (-70 to 1,177)

13 (-0.87 to 27)

-1.8 (-3.4 to -0.22)

2.2 (0.53 to 3.9)

    H3000’s -12 (-510 to 486)

1.5 (-9.8 to 13)

-0.16 (-1.4 to 1.1)

-0.19 (-1.6 to 1.2)

mean_PeakUpDownVel_mean * group_char
0.55 0.96
0.042 0.17
0.52 0.68
0.20 0.26
    mean_PeakUpDownVel_mean * H2000’s -1,162 (-3,440 to 1,115)

-57 (-108 to -7.3)

3.3 (-2.3 to 8.9)

-3.7 (-9.0 to 1.6)

    mean_PeakUpDownVel_mean * H3000’s 45 (-1,689 to 1,778)

5.7 (-33 to 44)

1.1 (-3.2 to 5.4)

1.4 (-2.7 to 5.5)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.6 (NA to NA)

0.60 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 636 (NA to NA)

14 (NA to NA)

1.5 (NA to NA)

1.4 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -0.68 (-9.6 to 8.2) 0.88 0.88 7.2 (-0.74 to 15) 0.075 0.30 -0.59 (-1.2 to 0.03) 0.061 0.25 0.12 (-0.51 to 0.75) 0.71 0.71
mean_APexc_COV 0.16 (-0.38 to 0.70) 0.56 0.74 -0.17 (-0.65 to 0.30) 0.47 0.63 0.01 (-0.02 to 0.05) 0.52 0.77 0.02 (-0.01 to 0.05) 0.12 0.30
group_char
0.083 0.33
0.45 0.63
0.60 0.77
0.15 0.30
    H1000’s







    H2000’s -8.2 (-22 to 5.5)

-7.2 (-20 to 5.1)

0.48 (-0.49 to 1.5)

0.87 (-0.13 to 1.9)

    H3000’s 7.7 (-5.2 to 21)

-6.0 (-18 to 5.8)

0.06 (-0.89 to 1.0)

0.77 (-0.21 to 1.8)

mean_APexc_COV * group_char
0.20 0.40
0.74 0.74
0.77 0.77
0.37 0.50
    mean_APexc_COV * H2000’s 0.17 (-0.53 to 0.86)

0.25 (-0.37 to 0.86)

-0.01 (-0.06 to 0.03)

-0.02 (-0.06 to 0.02)

    mean_APexc_COV * H3000’s -0.34 (-0.98 to 0.31)

0.15 (-0.43 to 0.73)

0.00 (-0.04 to 0.05)

-0.03 (-0.07 to 0.01)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.6 (NA to NA)

0.47 (NA to NA)

0.99 (NA to NA)

Residual.sd__Observation 11 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.48 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.8 (-5.8 to 9.5) 0.64 0.98 3.3 (-3.3 to 9.9) 0.32 0.96 -0.23 (-0.74 to 0.28) 0.38 0.87 0.44 (-0.10 to 0.99) 0.11 0.45
mean_APexc_mean 2.0 (-134 to 138) 0.98 0.98 20 (-96 to 136) 0.73 0.96 -3.2 (-12 to 5.3) 0.46 0.87 1.3 (-5.7 to 8.3) 0.72 0.89
group_char
0.75 0.98
0.86 0.96
0.96 0.96
0.39 0.79
    H1000’s







    H2000’s -1.4 (-12 to 9.5)

-1.8 (-11 to 7.8)

-0.07 (-0.82 to 0.69)

0.59 (-0.26 to 1.4)

    H3000’s 2.3 (-7.5 to 12)

-2.4 (-11 to 6.3)

0.05 (-0.65 to 0.75)

0.28 (-0.51 to 1.1)

mean_APexc_mean * group_char
0.89 0.98
0.96 0.96
0.65 0.87
0.89 0.89
    mean_APexc_mean * H2000’s -43 (-255 to 168)

-17 (-200 to 167)

6.5 (-7.3 to 20)

-1.5 (-13 to 10)

    mean_APexc_mean * H3000’s -40 (-237 to 156)

-26 (-198 to 147)

2.3 (-11 to 15)

1.6 (-9.7 to 13)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.5 (NA to NA)

0.48 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 11 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.9 (-2.1 to 10) 0.20 0.27 3.5 (-2.3 to 9.3) 0.24 0.60 -0.61 (-1.1 to -0.12) 0.015 0.060 0.67 (0.09 to 1.2) 0.022 0.089
mean_MLexc_COV -0.14 (-0.53 to 0.25) 0.48 0.48 0.06 (-0.31 to 0.44) 0.75 0.75 0.01 (-0.02 to 0.04) 0.36 0.36 -0.01 (-0.04 to 0.02) 0.47 0.54
group_char
<0.001 0.004
0.33 0.60
0.039 0.078
0.38 0.54
    H1000’s







    H2000’s -14 (-23 to -4.2)

-6.7 (-16 to 2.2)

0.85 (0.12 to 1.6)

0.58 (-0.28 to 1.4)

    H3000’s 5.6 (-4.3 to 15)

-2.2 (-11 to 6.9)

-0.01 (-0.75 to 0.74)

0.08 (-0.77 to 0.93)

mean_MLexc_COV * group_char
0.009 0.017
0.45 0.60
0.061 0.081
0.54 0.54
    mean_MLexc_COV * H2000’s 0.73 (0.10 to 1.4)

0.28 (-0.29 to 0.86)

-0.04 (-0.09 to 0.00)

-0.01 (-0.05 to 0.04)

    mean_MLexc_COV * H3000’s -0.35 (-1.0 to 0.31)

-0.11 (-0.71 to 0.49)

0.01 (-0.03 to 0.06)

0.02 (-0.02 to 0.06)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.4 (NA to NA)

0.45 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 10 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.48 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 0.39 (-5.9 to 6.7) 0.90 0.92 5.3 (-0.38 to 11) 0.067 0.27 -0.18 (-0.64 to 0.27) 0.43 0.86 0.33 (-0.19 to 0.86) 0.21 0.40
mean_MLexc_mean 19 (-55 to 92) 0.62 0.92 -11 (-76 to 53) 0.73 0.97 -2.7 (-7.6 to 2.2) 0.28 0.86 2.2 (-1.9 to 6.4) 0.30 0.40
group_char
0.92 0.92
0.52 0.97
0.98 0.98
0.30 0.40
    H1000’s







    H2000’s 1.2 (-7.8 to 10)

-3.7 (-12 to 4.5)

0.05 (-0.60 to 0.71)

0.59 (-0.19 to 1.4)

    H3000’s 1.7 (-6.8 to 10)

-4.3 (-12 to 3.5)

0.00 (-0.64 to 0.63)

0.42 (-0.34 to 1.2)

mean_MLexc_mean * group_char
0.54 0.92
0.97 0.97
0.72 0.95
0.89 0.89
    mean_MLexc_mean * H2000’s -52 (-151 to 46)

12 (-74 to 98)

2.5 (-4.0 to 9.0)

-1.2 (-6.7 to 4.3)

    mean_MLexc_mean * H3000’s -13 (-108 to 83)

7.1 (-78 to 92)

2.3 (-4.2 to 8.8)

-1.2 (-6.7 to 4.3)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.6 (NA to NA)

0.47 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 11 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.48 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.2 (-7.3 to 9.7) 0.78 0.86 7.5 (2.2 to 13) 0.006 0.022 -0.36 (-0.80 to 0.07) 0.10 0.41 0.54 (0.05 to 1.0) 0.030 0.12
mean_StepDur 0.81 (-7.9 to 9.5) 0.86 0.86 -3.4 (-8.6 to 1.9) 0.21 0.42 -0.04 (-0.45 to 0.36) 0.83 0.83 -0.03 (-0.34 to 0.27) 0.84 0.90
group_char
0.32 0.64
0.32 0.43
0.53 0.72
0.90 0.90
    H1000’s







    H2000’s 6.6 (-9.0 to 22)

-5.2 (-15 to 4.6)

0.14 (-0.66 to 0.94)

0.19 (-0.65 to 1.0)

    H3000’s -7.0 (-22 to 7.6)

-6.4 (-16 to 2.9)

0.45 (-0.33 to 1.2)

0.13 (-0.68 to 0.94)

mean_StepDur * group_char
0.073 0.29
0.84 0.84
0.54 0.72
0.41 0.82
    mean_StepDur * H2000’s -13 (-32 to 5.8)

2.6 (-9.0 to 14)

0.14 (-0.75 to 1.0)

0.42 (-0.27 to 1.1)

    mean_StepDur * H3000’s 15 (-4.3 to 34)

2.8 (-9.1 to 15)

-0.48 (-1.4 to 0.47)

0.31 (-0.44 to 1.1)

subj_char.sd__(Intercept) 3.0 (NA to NA)

3.6 (NA to NA)

0.51 (NA to NA)

1.0 (NA to NA)

Residual.sd__Observation 14 (NA to NA)

8.5 (NA to NA)

0.64 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 0.62 (-5.0 to 6.2) 0.83 0.95 6.3 (1.5 to 11) 0.011 0.042 -0.28 (-0.66 to 0.11) 0.16 0.65 0.52 (0.04 to 0.99) 0.033 0.13
mean_UDexc_COV 0.11 (-0.31 to 0.53) 0.62 0.95 -0.16 (-0.51 to 0.20) 0.39 0.51 -0.01 (-0.04 to 0.02) 0.43 0.86 0.00 (-0.02 to 0.02) 0.98 0.98
group_char
0.59 0.95
0.29 0.51
0.95 0.95
0.43 0.87
    H1000’s







    H2000’s -2.9 (-11 to 5.5)

-4.8 (-12 to 2.6)

0.09 (-0.50 to 0.68)

0.47 (-0.28 to 1.2)

    H3000’s 2.0 (-7.0 to 11)

-5.5 (-13 to 2.3)

0.00 (-0.62 to 0.62)

0.33 (-0.41 to 1.1)

mean_UDexc_COV * group_char
0.95 0.95
0.78 0.78
0.71 0.94
0.98 0.98
    mean_UDexc_COV * H2000’s -0.05 (-0.64 to 0.54)

0.16 (-0.33 to 0.66)

0.01 (-0.02 to 0.05)

0.00 (-0.03 to 0.03)

    mean_UDexc_COV * H3000’s -0.10 (-0.75 to 0.54)

0.14 (-0.40 to 0.69)

0.01 (-0.03 to 0.05)

0.00 (-0.03 to 0.03)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.6 (NA to NA)

0.47 (NA to NA)

0.99 (NA to NA)

Residual.sd__Observation 11 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.3 (-2.9 to 9.4) 0.30 0.40 2.8 (-2.6 to 8.1) 0.31 0.87 -0.58 (-1.0 to -0.16) 0.007 0.027 0.54 (0.05 to 1.0) 0.032 0.13
mean_UDexc_mean -58 (-306 to 191) 0.65 0.65 70 (-140 to 280) 0.51 0.87 7.5 (-7.7 to 23) 0.33 0.45 -0.90 (-13 to 12) 0.89 0.89
group_char
0.011 0.045
0.81 0.87
0.21 0.43
0.22 0.44
    H1000’s







    H2000’s -10 (-20 to -1.1)

-2.5 (-11 to 5.6)

0.57 (-0.07 to 1.2)

0.68 (-0.09 to 1.5)

    H3000’s 3.8 (-5.2 to 13)

-2.0 (-9.9 to 6.0)

0.24 (-0.39 to 0.87)

0.21 (-0.54 to 0.95)

mean_UDexc_mean * group_char
0.075 0.15
0.87 0.87
0.47 0.47
0.46 0.61
    mean_UDexc_mean * H2000’s 292 (-72 to 656)

-10 (-319 to 299)

-14 (-36 to 9.0)

-7.2 (-26 to 11)

    mean_UDexc_mean * H3000’s -128 (-485 to 229)

-76 (-381 to 229)

-2.5 (-25 to 20)

5.0 (-13 to 24)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.5 (NA to NA)

0.47 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 10 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.1 (-5.9 to 8.2) 0.75 0.81 7.1 (2.6 to 12) 0.002 0.008 -0.36 (-0.74 to 0.02) 0.062 0.25 0.53 (0.07 to 1.0) 0.024 0.095
mean_StanceDur 0.62 (-4.5 to 5.8) 0.81 0.81 -2.1 (-5.3 to 1.0) 0.18 0.32 -0.03 (-0.27 to 0.21) 0.79 0.79 -0.02 (-0.20 to 0.17) 0.87 0.87
group_char
0.45 0.81
0.24 0.32
0.56 0.79
0.76 0.87
    H1000’s







    H2000’s 3.9 (-9.1 to 17)

-4.9 (-13 to 3.3)

0.17 (-0.51 to 0.85)

0.28 (-0.50 to 1.1)

    H3000’s -5.5 (-18 to 6.8)

-6.1 (-14 to 1.7)

0.36 (-0.30 to 1.0)

0.17 (-0.58 to 0.92)

mean_StanceDur * group_char
0.088 0.35
0.83 0.83
0.60 0.79
0.47 0.87
    mean_StanceDur * H2000’s -7.0 (-18 to 4.4)

1.6 (-5.3 to 8.6)

0.07 (-0.46 to 0.61)

0.22 (-0.19 to 0.62)

    mean_StanceDur * H3000’s 9.2 (-2.4 to 21)

1.8 (-5.4 to 8.9)

-0.26 (-0.82 to 0.30)

0.18 (-0.25 to 0.62)

subj_char.sd__(Intercept) 3.1 (NA to NA)

3.6 (NA to NA)

0.51 (NA to NA)

1.0 (NA to NA)

Residual.sd__Observation 14 (NA to NA)

8.5 (NA to NA)

0.64 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.2 (-7.3 to 9.7) 0.78 0.86 7.5 (2.2 to 13) 0.006 0.022 -0.36 (-0.80 to 0.07) 0.10 0.41 0.54 (0.05 to 1.0) 0.030 0.12
mean_GaitCycleDur 0.40 (-3.9 to 4.7) 0.86 0.86 -1.7 (-4.3 to 0.96) 0.21 0.43 -0.02 (-0.22 to 0.18) 0.83 0.83 -0.02 (-0.17 to 0.14) 0.84 0.89
group_char
0.32 0.64
0.32 0.43
0.53 0.72
0.89 0.89
    H1000’s







    H2000’s 6.5 (-9.1 to 22)

-5.2 (-15 to 4.5)

0.14 (-0.66 to 0.94)

0.19 (-0.65 to 1.0)

    H3000’s -7.1 (-22 to 7.6)

-6.4 (-16 to 2.9)

0.44 (-0.33 to 1.2)

0.13 (-0.68 to 0.95)

mean_GaitCycleDur * group_char
0.073 0.29
0.84 0.84
0.54 0.72
0.42 0.84
    mean_GaitCycleDur * H2000’s -6.5 (-16 to 2.9)

1.3 (-4.5 to 7.1)

0.07 (-0.37 to 0.52)

0.21 (-0.14 to 0.55)

    mean_GaitCycleDur * H3000’s 7.4 (-2.1 to 17)

1.4 (-4.6 to 7.4)

-0.24 (-0.71 to 0.24)

0.15 (-0.22 to 0.52)

subj_char.sd__(Intercept) 3.0 (NA to NA)

3.6 (NA to NA)

0.51 (NA to NA)

1.0 (NA to NA)

Residual.sd__Observation 14 (NA to NA)

8.5 (NA to NA)

0.64 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 6
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.8 (-2.2 to 7.7) 0.28 0.37 2.8 (-1.5 to 7.2) 0.20 0.81 -0.49 (-0.84 to -0.15) 0.005 0.021 0.52 (0.07 to 0.97) 0.024 0.10
mean_PeakUpDownVel_mean -3.6 (-23 to 16) 0.72 0.72 6.8 (-9.4 to 23) 0.41 0.82 0.40 (-0.77 to 1.6) 0.50 0.63 -0.03 (-0.96 to 0.90) 0.95 0.95
group_char
0.010 0.041
0.76 0.85
0.27 0.53
0.21 0.41
    H1000’s







    H2000’s -8.9 (-17 to -1.1)

-2.1 (-8.9 to 4.7)

0.45 (-0.10 to 1.0)

0.65 (-0.07 to 1.4)

    H3000’s 3.5 (-4.1 to 11)

-2.2 (-8.9 to 4.4)

0.22 (-0.32 to 0.76)

0.30 (-0.39 to 1.0)

mean_PeakUpDownVel_mean * group_char
0.085 0.17
0.85 0.85
0.63 0.63
0.61 0.82
    mean_PeakUpDownVel_mean * H2000’s 22 (-6.8 to 50)

-3.2 (-27 to 20)

-0.81 (-2.5 to 0.89)

-0.55 (-1.9 to 0.82)

    mean_PeakUpDownVel_mean * H3000’s -9.5 (-37 to 18)

-6.7 (-29 to 16)

-0.19 (-1.8 to 1.5)

0.10 (-1.2 to 1.4)

subj_char.sd__(Intercept) 0.00 (NA to NA)

3.5 (NA to NA)

0.47 (NA to NA)

0.99 (NA to NA)

Residual.sd__Observation 10 (NA to NA)

8.6 (NA to NA)

0.61 (NA to NA)

0.49 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -11 (-54 to 33) 0.64 0.94 1.0 (-1.3 to 3.3) 0.38 0.89 -0.65 (-1.7 to 0.37) 0.21 0.84 2.2 (0.97 to 3.5) <0.001 0.002
mean_APexc_COV -0.10 (-2.8 to 2.6) 0.94 0.94 -0.04 (-0.18 to 0.10) 0.58 0.89 0.00 (-0.06 to 0.06) 0.90 0.90 -0.02 (-0.09 to 0.05) 0.59 0.59
group_char
0.81 0.94
0.85 0.89
0.48 0.90
0.13 0.19
    H1000’s







    H2000’s -18 (-95 to 58)

-1.1 (-5.2 to 2.9)

0.28 (-1.6 to 2.2)

1.7 (-0.68 to 4.2)

    H3000’s 6.0 (-52 to 64)

-0.62 (-3.7 to 2.5)

0.86 (-0.54 to 2.3)

-0.75 (-2.5 to 0.99)

mean_APexc_COV * group_char
0.70 0.94
0.89 0.89
0.83 0.90
0.14 0.19
    mean_APexc_COV * H2000’s 1.4 (-2.5 to 5.2)

0.05 (-0.15 to 0.25)

-0.02 (-0.11 to 0.07)

-0.04 (-0.15 to 0.07)

    mean_APexc_COV * H3000’s 0.07 (-3.0 to 3.1)

0.03 (-0.13 to 0.19)

-0.02 (-0.09 to 0.05)

0.05 (-0.03 to 0.13)

subj_char.sd__(Intercept) 17 (NA to NA)

1.2 (NA to NA)

0.84 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -17 (-53 to 20) 0.37 0.83 1.6 (-0.26 to 3.5) 0.091 0.34 -0.59 (-1.4 to 0.24) 0.16 0.34 1.6 (0.60 to 2.7) 0.002 0.008
mean_APexc_mean 79 (-551 to 709) 0.81 0.83 -22 (-54 to 9.6) 0.17 0.34 0.03 (-13 to 14)
0.99
0.99
5.1 (-11 to 21) 0.53 0.89
group_char
0.83 0.83
0.47 0.63
0.17 0.34
0.75 0.89
    H1000’s







    H2000’s 5.3 (-48 to 59)

-1.3 (-4.1 to 1.4)

-0.51 (-1.8 to 0.75)

0.54 (-1.0 to 2.1)

    H3000’s -9.6 (-57 to 38)

-1.5 (-3.9 to 1.0)

0.64 (-0.48 to 1.8)

0.47 (-0.96 to 1.9)

mean_APexc_mean * group_char
0.67 0.83
0.63 0.63
0.42 0.56
0.89 0.89
    mean_APexc_mean * H2000’s 141 (-873 to 1,156)

18 (-34 to 70)

9.1 (-13 to 31)

5.0 (-21 to 31)

    mean_APexc_mean * H3000’s 422 (-511 to 1,356)

22 (-26 to 70)

-6.9 (-28 to 14)

-1.7 (-27 to 23)

subj_char.sd__(Intercept) 16 (NA to NA)

1.2 (NA to NA)

0.82 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -8.2 (-44 to 27) 0.65 0.82 0.66 (-1.2 to 2.5) 0.49 0.88 -0.07 (-0.95 to 0.82) 0.88 0.88 1.8 (0.65 to 2.9) 0.002 0.008
mean_MLexc_COV -0.29 (-2.7 to 2.2) 0.82 0.82 -0.02 (-0.15 to 0.11) 0.76 0.88 -0.04 (-0.10 to 0.02) 0.20 0.81 0.01 (-0.06 to 0.08) 0.79 0.79
group_char
0.46 0.82
0.78 0.88
0.42 0.83
0.045 0.090
    H1000’s







    H2000’s 19 (-33 to 71)

-0.98 (-3.7 to 1.8)

-0.60 (-1.9 to 0.68)

2.1 (0.44 to 3.7)

    H3000’s -14 (-64 to 36)

-0.59 (-3.2 to 2.0)

0.23 (-0.99 to 1.5)

0.87 (-0.67 to 2.4)

mean_MLexc_COV * group_char
0.48 0.82
0.88 0.88
0.64 0.85
0.16 0.21
    mean_MLexc_COV * H2000’s -0.54 (-4.0 to 2.9)

0.05 (-0.13 to 0.23)

0.04 (-0.04 to 0.12)

-0.10 (-0.19 to 0.00)

    mean_MLexc_COV * H3000’s 1.5 (-1.9 to 4.9)

0.02 (-0.15 to 0.20)

0.01 (-0.07 to 0.09)

-0.04 (-0.13 to 0.06)

subj_char.sd__(Intercept) 17 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.3 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -31 (-63 to 1.8) 0.064 0.26 1.3 (-0.39 to 3.0) 0.13 0.51 -0.77 (-1.5 to 0.00) 0.049 0.20 1.8 (0.87 to 2.8) <0.001 <0.001
mean_MLexc_mean 222 (-143 to 586) 0.23 0.47 -11 (-30 to 7.8) 0.25 0.51 2.2 (-5.9 to 10) 0.60 0.67 0.82 (-8.6 to 10) 0.87 0.88
group_char
0.69 0.90
0.58 0.69
0.27 0.54
0.88 0.88
    H1000’s







    H2000’s 20 (-26 to 66)

-1.0 (-3.4 to 1.4)

-0.30 (-1.4 to 0.81)

0.34 (-1.1 to 1.8)

    H3000’s 13 (-30 to 55)

-1.1 (-3.3 to 1.1)

0.54 (-0.48 to 1.6)

0.28 (-1.0 to 1.6)

mean_MLexc_mean * group_char
0.90 0.90
0.69 0.69
0.67 0.67
0.75 0.88
    mean_MLexc_mean * H2000’s -111 (-596 to 374)

8.6 (-16 to 33)

2.2 (-8.5 to 13)

4.3 (-8.3 to 17)

    mean_MLexc_mean * H3000’s -73 (-544 to 398)

10 (-14 to 35)

-2.3 (-13 to 8.2)

0.58 (-12 to 13)

subj_char.sd__(Intercept) 16 (NA to NA)

1.2 (NA to NA)

0.82 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -20 (-50 to 9.3) 0.18 0.72 1.2 (-0.27 to 2.8) 0.11 0.43 -0.43 (-1.1 to 0.25) 0.22 0.58 1.7 (0.80 to 2.5) <0.001 <0.001
mean_StepDur 8.9 (-21 to 39) 0.56 0.97 -0.94 (-2.4 to 0.56) 0.22 0.44 -0.18 (-0.80 to 0.44) 0.58 0.58 0.27 (-0.44 to 0.99) 0.45 0.85
group_char
0.97 0.97
0.66 0.83
0.32 0.58
0.85 0.85
    H1000’s







    H2000’s 1.1 (-53 to 55)

-0.88 (-3.6 to 1.9)

-0.76 (-2.0 to 0.45)

0.41 (-1.1 to 1.9)

    H3000’s -5.3 (-54 to 44)

-1.1 (-3.6 to 1.4)

0.24 (-0.88 to 1.4)

0.28 (-1.1 to 1.7)

mean_StepDur * group_char
0.78 0.97
0.83 0.83
0.44 0.58
0.83 0.85
    mean_StepDur * H2000’s 14 (-48 to 76)

0.56 (-2.5 to 3.7)

0.84 (-0.45 to 2.1)

0.46 (-1.0 to 2.0)

    mean_StepDur * H3000’s 20 (-42 to 82)

0.90 (-2.2 to 4.0)

0.12 (-1.2 to 1.4)

0.16 (-1.4 to 1.7)

subj_char.sd__(Intercept) 17 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 49 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -19 (-45 to 7.2) 0.16 0.63 1.2 (-0.09 to 2.6) 0.067 0.27 -0.67 (-1.3 to -0.06) 0.033 0.13 1.8 (1.0 to 2.6) <0.001 <0.001
mean_UDexc_COV 0.52 (-1.3 to 2.4) 0.58 0.99 -0.07 (-0.16 to 0.02) 0.15 0.30 0.01 (-0.03 to 0.05) 0.73 0.91 0.01 (-0.04 to 0.05) 0.76 0.98
group_char
0.99 0.99
0.48 0.57
0.79 0.91
0.57 0.98
    H1000’s







    H2000’s 2.4 (-38 to 42)

-1.1 (-3.1 to 1.0)

-0.19 (-1.2 to 0.77)

0.69 (-0.59 to 2.0)

    H3000’s 3.1 (-37 to 43)

-1.1 (-3.2 to 0.97)

0.17 (-0.78 to 1.1)

0.36 (-0.87 to 1.6)

mean_UDexc_COV * group_char
0.90 0.99
0.57 0.57
0.91 0.91
0.98 0.98
    mean_UDexc_COV * H2000’s 0.65 (-2.1 to 3.4)

0.06 (-0.08 to 0.20)

0.01 (-0.05 to 0.07)

0.00 (-0.07 to 0.07)

    mean_UDexc_COV * H3000’s 0.21 (-2.5 to 3.0)

0.07 (-0.07 to 0.21)

0.01 (-0.05 to 0.07)

0.00 (-0.07 to 0.07)

subj_char.sd__(Intercept) 16 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -14 (-44 to 15) 0.34 0.87 -0.48 (-2.0 to 1.0) 0.53 0.84 -0.67 (-1.3 to 0.01) 0.053 0.21 2.3 (1.4 to 3.1) <0.001 <0.001
mean_UDexc_mean 91 (-1,037 to 1,219) 0.87 0.87 36 (-20 to 93) 0.21 0.83 3.5 (-20 to 27) 0.77 0.87 -15 (-42 to 13) 0.30 0.60
group_char
0.46 0.87
0.84 0.84
0.56 0.87
0.65 0.86
    H1000’s







    H2000’s 28 (-18 to 73)

0.34 (-2.0 to 2.7)

0.14 (-0.94 to 1.2)

0.66 (-0.73 to 2.0)

    H3000’s 18 (-23 to 60)

0.65 (-1.5 to 2.8)

0.53 (-0.45 to 1.5)

0.22 (-1.0 to 1.5)

mean_UDexc_mean * group_char
0.72 0.87
0.63 0.84
0.87 0.87
0.97 0.97
    mean_UDexc_mean * H2000’s -684 (-2,430 to 1,061)

-28 (-116 to 60)

-9.2 (-46 to 28)

3.3 (-40 to 46)

    mean_UDexc_mean * H3000’s -464 (-2,041 to 1,112)

-38 (-117 to 42)

-7.2 (-41 to 27)

4.8 (-35 to 44)

subj_char.sd__(Intercept) 16 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -18 (-43 to 6.7) 0.15 0.61 1.1 (-0.16 to 2.4) 0.087 0.35 -0.45 (-1.0 to 0.14) 0.14 0.48 1.7 (0.93 to 2.5) <0.001 <0.001
mean_StanceDur 4.9 (-13 to 23) 0.59 0.94 -0.59 (-1.5 to 0.30) 0.19 0.39 -0.11 (-0.48 to 0.25) 0.55 0.55 0.17 (-0.26 to 0.59) 0.44 0.89
group_char
0.94 0.94
0.63 0.83
0.24 0.48
0.69 0.92
    H1000’s







    H2000’s 3.7 (-41 to 49)

-0.83 (-3.1 to 1.5)

-0.68 (-1.7 to 0.35)

0.58 (-0.76 to 1.9)

    H3000’s -5.3 (-46 to 36)

-0.93 (-3.0 to 1.2)

0.28 (-0.67 to 1.2)

0.29 (-0.94 to 1.5)

mean_StanceDur * group_char
0.73 0.94
0.83 0.83
0.37 0.49
0.92 0.92
    mean_StanceDur * H2000’s 8.0 (-29 to 45)

0.38 (-1.5 to 2.2)

0.54 (-0.22 to 1.3)

0.18 (-0.70 to 1.1)

    mean_StanceDur * H3000’s 14 (-23 to 52)

0.53 (-1.3 to 2.4)

0.05 (-0.73 to 0.83)

0.10 (-0.81 to 1.0)

subj_char.sd__(Intercept) 17 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -20 (-50 to 9.3) 0.18 0.71 1.2 (-0.27 to 2.7) 0.11 0.43 -0.42 (-1.1 to 0.25) 0.22 0.57 1.7 (0.80 to 2.5) <0.001 <0.001
mean_GaitCycleDur 4.5 (-11 to 20) 0.56 0.97 -0.47 (-1.2 to 0.28) 0.22 0.44 -0.09 (-0.40 to 0.22) 0.57 0.57 0.14 (-0.22 to 0.49) 0.45 0.85
group_char
0.97 0.97
0.66 0.83
0.31 0.57
0.85 0.85
    H1000’s







    H2000’s 1.2 (-52 to 55)

-0.87 (-3.6 to 1.9)

-0.76 (-2.0 to 0.44)

0.41 (-1.1 to 1.9)

    H3000’s -5.2 (-54 to 44)

-1.1 (-3.6 to 1.4)

0.23 (-0.88 to 1.4)

0.27 (-1.1 to 1.7)

mean_GaitCycleDur * group_char
0.78 0.97
0.83 0.83
0.44 0.57
0.83 0.85
    mean_GaitCycleDur * H2000’s 7.1 (-24 to 38)

0.28 (-1.3 to 1.8)

0.42 (-0.22 to 1.1)

0.23 (-0.51 to 0.97)

    mean_GaitCycleDur * H3000’s 10 (-21 to 41)

0.44 (-1.1 to 2.0)

0.06 (-0.60 to 0.72)

0.08 (-0.69 to 0.85)

subj_char.sd__(Intercept) 17 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 49 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 7
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -13 (-37 to 10) 0.27 0.91 -0.49 (-1.7 to 0.74) 0.44 0.61 -0.55 (-1.1 to 0.01) 0.056 0.22 2.2 (1.4 to 2.9) <0.001 <0.001
mean_PeakUpDownVel_mean 4.8 (-83 to 93) 0.91 0.91 3.7 (-0.65 to 8.1) 0.10 0.38 -0.13 (-1.9 to 1.7) 0.89 0.93 -1.2 (-3.3 to 0.90) 0.26 0.47
group_char
0.46 0.91
0.79 0.79
0.55 0.93
0.35 0.47
    H1000’s







    H2000’s 21 (-17 to 60)

0.36 (-1.6 to 2.3)

0.05 (-0.87 to 0.98)

0.89 (-0.33 to 2.1)

    H3000’s 18 (-16 to 52)

0.62 (-1.1 to 2.4)

0.44 (-0.39 to 1.3)

0.21 (-0.88 to 1.3)

mean_PeakUpDownVel_mean * group_char
0.76 0.91
0.46 0.61
0.93 0.93
0.81 0.81
    mean_PeakUpDownVel_mean * H2000’s -39 (-175 to 97)

-2.9 (-9.7 to 3.8)

-0.52 (-3.3 to 2.3)

-0.51 (-3.8 to 2.8)

    mean_PeakUpDownVel_mean * H3000’s -43 (-164 to 78)

-3.7 (-9.8 to 2.3)

-0.31 (-2.8 to 2.2)

0.56 (-2.4 to 3.5)

subj_char.sd__(Intercept) 16 (NA to NA)

1.2 (NA to NA)

0.83 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 50 (NA to NA)

2.5 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -7.6 (-47 to 32) 0.71 0.92 0.61 (-0.93 to 2.1) 0.44 0.68 -0.27 (-1.1 to 0.57) 0.53 0.62 0.86 (-0.18 to 1.9) 0.10 0.21
mean_APexc_COV 0.67 (-1.7 to 3.1) 0.59 0.92 -0.02 (-0.11 to 0.07) 0.65 0.68 -0.03 (-0.08 to 0.02) 0.28 0.62 0.02 (-0.04 to 0.07) 0.49 0.49
group_char
0.83 0.92
0.62 0.68
0.62 0.62
0.060 0.21
    H1000’s







    H2000’s -18 (-80 to 43)

-1.2 (-3.6 to 1.2)

-0.67 (-2.0 to 0.67)

2.0 (0.34 to 3.7)

    H3000’s -3.7 (-62 to 54)

-0.56 (-2.8 to 1.7)

-0.24 (-1.5 to 1.1)

0.56 (-1.1 to 2.2)

mean_APexc_COV * group_char
0.92 0.92
0.68 0.68
0.31 0.62
0.19 0.25
    mean_APexc_COV * H2000’s 0.05 (-3.1 to 3.2)

0.05 (-0.07 to 0.18)

0.05 (-0.01 to 0.12)

-0.06 (-0.13 to 0.02)

    mean_APexc_COV * H3000’s -0.44 (-3.4 to 2.5)

0.04 (-0.07 to 0.16)

0.03 (-0.03 to 0.09)

0.00 (-0.07 to 0.07)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.72 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.94 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 7.6 (-27 to 42) 0.67 0.88 0.31 (-1.0 to 1.6) 0.65 0.86 -0.65 (-1.4 to 0.05) 0.068 0.27 0.97 (0.09 to 1.9) 0.031 0.13
mean_APexc_mean -82 (-686 to 522) 0.79 0.88 -0.82 (-24 to 22) 0.94 0.94 -1.0 (-12 to 10) 0.86 0.86 3.7 (-8.7 to 16) 0.56 0.74
group_char
0.65 0.88
0.16 0.32
0.61 0.86
0.43 0.74
    H1000’s







    H2000’s -23 (-73 to 27)

1.8 (-0.13 to 3.7)

0.50 (-0.55 to 1.5)

0.81 (-0.54 to 2.2)

    H3000’s -8.1 (-54 to 38)

0.43 (-1.3 to 2.2)

0.05 (-0.96 to 1.1)

0.67 (-0.63 to 2.0)

mean_APexc_mean * group_char
0.88 0.88
0.054 0.21
0.65 0.86
0.97 0.97
    mean_APexc_mean * H2000’s 204 (-764 to 1,172)

-43 (-80 to -6.1)

-4.6 (-23 to 14)

2.1 (-19 to 23)

    mean_APexc_mean * H3000’s -49 (-983 to 884)

-3.4 (-39 to 32)

5.6 (-14 to 25)

2.3 (-19 to 24)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.75 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.0 (NA to NA)

0.93 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.8 (-31 to 25) 0.84 0.84 0.31 (-0.77 to 1.4) 0.57 0.76 -0.62 (-1.3 to 0.07) 0.080 0.32 1.4 (0.45 to 2.3) 0.003 0.014
mean_MLexc_COV 0.41 (-1.4 to 2.2) 0.66 0.84 0.00 (-0.07 to 0.07) 0.93 0.93 -0.01 (-0.05 to 0.04) 0.78 0.78 -0.01 (-0.06 to 0.04) 0.59 0.59
group_char
0.17 0.55
0.29 0.76
0.65 0.78
0.052 0.10
    H1000’s







    H2000’s -21 (-64 to 23)

-1.2 (-2.9 to 0.53)

-0.04 (-1.1 to 0.99)

1.6 (0.22 to 2.9)

    H3000’s -43 (-88 to 2.1)

0.20 (-1.6 to 2.0)

0.43 (-0.63 to 1.5)

0.21 (-1.2 to 1.6)

mean_MLexc_COV * group_char
0.28 0.55
0.42 0.76
0.59 0.78
0.076 0.10
    mean_MLexc_COV * H2000’s 0.52 (-2.3 to 3.4)

0.07 (-0.04 to 0.18)

0.02 (-0.04 to 0.09)

-0.05 (-0.12 to 0.02)

    mean_MLexc_COV * H3000’s 2.4 (-0.57 to 5.3)

0.01 (-0.11 to 0.12)

-0.01 (-0.07 to 0.06)

0.03 (-0.04 to 0.11)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.94 (NA to NA)

0.99 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 18 (-11 to 48) 0.22 0.56 0.31 (-0.82 to 1.4) 0.59 0.79 -0.72 (-1.4 to -0.07) 0.030 0.12 0.77 (-0.06 to 1.6) 0.069 0.28
mean_MLexc_mean -188 (-529 to 152) 0.28 0.56 -0.51 (-14 to 13) 0.94 0.94 0.08 (-6.9 to 7.0) 0.98 0.98 4.9 (-2.8 to 13) 0.21 0.28
group_char
0.46 0.61
0.10 0.19
0.80 0.98
0.15 0.28
    H1000’s







    H2000’s -27 (-69 to 16)

1.4 (-0.20 to 3.0)

0.28 (-0.64 to 1.2)

0.80 (-0.42 to 2.0)

    H3000’s -9.1 (-50 to 31)

-0.22 (-1.8 to 1.3)

0.03 (-0.89 to 0.95)

1.2 (-0.04 to 2.4)

mean_MLexc_mean * group_char
0.72 0.72
0.017 0.069
0.75 0.98
0.43 0.43
    mean_MLexc_mean * H2000’s 163 (-301 to 628)

-18 (-36 to 0.07)

0.17 (-9.0 to 9.3)

0.30 (-9.8 to 10)

    mean_MLexc_mean * H3000’s 6.4 (-455 to 468)

6.3 (-11 to 24)

3.2 (-6.4 to 13)

-5.8 (-17 to 5.0)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.0 (NA to NA)

0.94 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 12 (-27 to 51) 0.55 0.92 0.28 (-0.82 to 1.4) 0.62 0.83 -0.61 (-1.2 to 0.01) 0.053 0.21 0.93 (0.15 to 1.7) 0.019 0.076
mean_StepDur -9.7 (-50 to 31) 0.64 0.92 -0.01 (-1.1 to 1.1) 0.98 0.98 -0.11 (-0.68 to 0.47) 0.72 0.84 0.27 (-0.31 to 0.85) 0.36 0.53
group_char
0.73 0.92
0.061 0.12
0.62 0.84
0.53 0.53
    H1000’s







    H2000’s -28 (-97 to 41)

2.2 (0.30 to 4.2)

0.45 (-0.64 to 1.5)

0.76 (-0.56 to 2.1)

    H3000’s -6.7 (-77 to 64)

0.08 (-1.9 to 2.0)

0.45 (-0.70 to 1.6)

0.17 (-1.2 to 1.5)

mean_StepDur * group_char
0.92 0.92
0.020 0.080
0.84 0.84
0.44 0.53
    mean_StepDur * H2000’s 17 (-66 to 100)

-3.2 (-5.5 to -0.84)

-0.22 (-1.4 to 0.98)

0.20 (-1.0 to 1.4)

    mean_StepDur * H3000’s 7.6 (-84 to 99)

0.31 (-2.3 to 2.9)

-0.39 (-1.8 to 1.0)

0.97 (-0.51 to 2.4)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.78 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 73 (NA to NA)

2.0 (NA to NA)

1.0 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 8.0 (-16 to 32) 0.51 0.66 0.31 (-0.61 to 1.2) 0.51 0.91 -0.70 (-1.2 to -0.19) 0.008 0.030 0.96 (0.25 to 1.7) 0.008 0.033
mean_UDexc_COV -0.39 (-2.1 to 1.3) 0.66 0.66 0.00 (-0.07 to 0.06) 0.91 0.91 0.00 (-0.03 to 0.03) 0.98 0.98 0.02 (-0.02 to 0.05) 0.35 0.46
group_char
0.44 0.66
0.84 0.91
0.69 0.98
0.11 0.22
    H1000’s







    H2000’s -21 (-59 to 17)

0.39 (-1.1 to 1.9)

0.36 (-0.46 to 1.2)

1.1 (-0.02 to 2.2)

    H3000’s 4.8 (-35 to 44)

0.38 (-1.2 to 1.9)

0.19 (-0.66 to 1.0)

0.89 (-0.25 to 2.0)

mean_UDexc_COV * group_char
0.59 0.66
0.73 0.91
0.92 0.98
0.77 0.77
    mean_UDexc_COV * H2000’s 0.57 (-2.1 to 3.2)

-0.04 (-0.14 to 0.06)

0.00 (-0.05 to 0.05)

-0.02 (-0.07 to 0.03)

    mean_UDexc_COV * H3000’s -0.96 (-3.7 to 1.8)

-0.01 (-0.11 to 0.10)

0.01 (-0.05 to 0.06)

-0.01 (-0.07 to 0.04)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.94 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -3.1 (-31 to 25) 0.83 0.83 0.28 (-0.81 to 1.4) 0.62 0.82 -0.63 (-1.2 to -0.04) 0.036 0.14 1.4 (0.64 to 2.2) <0.001 0.001
mean_UDexc_mean 261 (-849 to 1,371) 0.64 0.83 -0.53 (-44 to 43) 0.98 0.98 -3.4 (-24 to 18) 0.75 0.97 -9.9 (-33 to 13) 0.39 0.52
group_char
0.42 0.83
0.10 0.40
0.97 0.97
0.12 0.25
    H1000’s







    H2000’s -20 (-62 to 23)

-1.3 (-3.0 to 0.35)

-0.11 (-1.0 to 0.79)

1.2 (0.00 to 2.4)

    H3000’s -26 (-68 to 15)

0.51 (-1.1 to 2.1)

-0.03 (-0.93 to 0.87)

0.82 (-0.37 to 2.0)

mean_UDexc_mean * group_char
0.69 0.83
0.20 0.40
0.53 0.97
0.73 0.73
    mean_UDexc_mean * H2000’s 265 (-1,397 to 1,927)

48 (-17 to 112)

17 (-14 to 48)

-13 (-47 to 21)

    mean_UDexc_mean * H3000’s 685 (-894 to 2,263)

-8.4 (-70 to 53)

13 (-18 to 44)

-3.6 (-37 to 30)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.73 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.94 (NA to NA)

0.99 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 11 (-21 to 44) 0.50 0.85 0.28 (-0.63 to 1.2) 0.54 0.73 -0.61 (-1.2 to -0.07) 0.027 0.11 0.94 (0.23 to 1.7) 0.009 0.037
mean_StanceDur -6.6 (-31 to 17) 0.59 0.85 -0.01 (-0.69 to 0.66) 0.97 0.97 -0.08 (-0.42 to 0.26) 0.66 0.95 0.19 (-0.16 to 0.53) 0.29 0.45
group_char
0.63 0.85
0.056 0.11
0.73 0.95
0.34 0.45
    H1000’s







    H2000’s -28 (-85 to 29)

1.9 (0.29 to 3.5)

0.31 (-0.62 to 1.2)

0.88 (-0.30 to 2.1)

    H3000’s -9.7 (-69 to 49)

0.11 (-1.5 to 1.8)

0.31 (-0.66 to 1.3)

0.40 (-0.81 to 1.6)

mean_StanceDur * group_char
0.86 0.86
0.012 0.048
0.95 0.95
0.58 0.58
    mean_StanceDur * H2000’s 12 (-37 to 62)

-2.0 (-3.4 to -0.62)

-0.03 (-0.73 to 0.68)

0.02 (-0.69 to 0.74)

    mean_StanceDur * H3000’s 8.9 (-47 to 64)

0.20 (-1.4 to 1.7)

-0.14 (-0.97 to 0.69)

0.45 (-0.40 to 1.3)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.78 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 73 (NA to NA)

2.0 (NA to NA)

1.0 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 12 (-27 to 51) 0.55 0.92 0.28 (-0.82 to 1.4) 0.62 0.83 -0.61 (-1.2 to 0.01) 0.053 0.21 0.93 (0.15 to 1.7) 0.019 0.076
mean_GaitCycleDur -4.9 (-25 to 15) 0.64 0.92 -0.01 (-0.57 to 0.56) 0.98 0.98 -0.05 (-0.34 to 0.24) 0.72 0.83 0.14 (-0.16 to 0.43) 0.36 0.52
group_char
0.73 0.92
0.063 0.13
0.62 0.83
0.52 0.52
    H1000’s







    H2000’s -28 (-97 to 41)

2.2 (0.29 to 4.2)

0.45 (-0.64 to 1.5)

0.76 (-0.55 to 2.1)

    H3000’s -7.0 (-77 to 63)

0.07 (-1.9 to 2.0)

0.46 (-0.69 to 1.6)

0.16 (-1.2 to 1.5)

mean_GaitCycleDur * group_char
0.92 0.92
0.021 0.083
0.83 0.83
0.44 0.52
    mean_GaitCycleDur * H2000’s 8.5 (-33 to 50)

-1.6 (-2.7 to -0.41)

-0.11 (-0.70 to 0.49)

0.09 (-0.51 to 0.70)

    mean_GaitCycleDur * H3000’s 4.0 (-42 to 50)

0.16 (-1.1 to 1.4)

-0.20 (-0.91 to 0.51)

0.48 (-0.25 to 1.2)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.78 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 73 (NA to NA)

2.0 (NA to NA)

1.0 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -1.6 (-24 to 21) 0.89 0.89 0.26 (-0.62 to 1.1) 0.56 0.74 -0.67 (-1.2 to -0.19) 0.007 0.027 1.4 (0.68 to 2.0) <0.001 <0.001
mean_PeakUpDownVel_mean 20 (-68 to 108) 0.66 0.89 0.01 (-3.4 to 3.4)
0.99
0.99
-0.16 (-1.8 to 1.4) 0.85 0.98 -0.78 (-2.5 to 0.92) 0.37 0.49
group_char
0.40 0.89
0.035 0.14
0.98 0.98
0.10 0.19
    H1000’s







    H2000’s -19 (-54 to 16)

-1.3 (-2.7 to 0.04)

0.06 (-0.69 to 0.82)

1.1 (0.05 to 2.2)

    H3000’s -22 (-57 to 13)

0.55 (-0.81 to 1.9)

0.05 (-0.71 to 0.82)

0.81 (-0.26 to 1.9)

mean_PeakUpDownVel_mean * group_char
0.78 0.89
0.077 0.15
0.67 0.98
0.77 0.77
    mean_PeakUpDownVel_mean * H2000’s 19 (-110 to 148)

4.5 (-0.43 to 9.5)

0.94 (-1.4 to 3.3)

-0.91 (-3.4 to 1.6)

    mean_PeakUpDownVel_mean * H3000’s 45 (-80 to 171)

-0.90 (-5.8 to 4.0)

0.90 (-1.4 to 3.2)

-0.24 (-2.8 to 2.3)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.73 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.94 (NA to NA)

0.99 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.8 (-26 to 21) 0.82 0.93 5.8 (-12 to 23) 0.52
0.99
0.15 (-1.2 to 1.5) 0.83 0.83 1.5 (0.02 to 2.9) 0.048 0.084
mean_APexc_COV -0.14 (-1.6 to 1.3) 0.85 0.93 -0.21 (-1.3 to 0.87) 0.70
0.99
-0.01 (-0.09 to 0.07) 0.74 0.83 -0.03 (-0.11 to 0.06) 0.50 0.50
group_char
0.93 0.93
0.99
0.99

0.71 0.83
0.032 0.084
    H1000’s







    H2000’s -1.2 (-35 to 32)

-0.09 (-25 to 25)

-0.71 (-2.6 to 1.2)

1.8 (-0.22 to 3.9)

    H3000’s 4.0 (-26 to 34)

0.05 (-23 to 23)

-0.62 (-2.3 to 1.1)

-0.69 (-2.6 to 1.2)

mean_APexc_COV * group_char
0.86 0.93
0.98
0.99

0.77 0.83
0.063 0.084
    mean_APexc_COV * H2000’s 0.42 (-1.4 to 2.2)

-0.01 (-1.3 to 1.3)

0.03 (-0.07 to 0.13)

-0.05 (-0.16 to 0.05)

    mean_APexc_COV * H3000’s 0.11 (-1.5 to 1.8)

0.08 (-1.1 to 1.3)

0.03 (-0.06 to 0.12)

0.04 (-0.06 to 0.14)

subj_char.sd__(Intercept) 2.9 (NA to NA)

4.6 (NA to NA)

0.51 (NA to NA)

0.86 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -0.01 (-19 to 19)
0.99
0.99
0.56 (-13 to 14) 0.94 0.94 -0.28 (-1.3 to 0.75) 0.59 0.71 1.1 (-0.01 to 2.3) 0.052 0.21
mean_APexc_mean -88 (-408 to 232) 0.59
0.99
33 (-196 to 263) 0.78 0.94 3.9 (-13 to 21) 0.65 0.71 -2.4 (-20 to 15) 0.79 0.86
group_char
0.89
0.99

0.18 0.39
0.71 0.71
0.63 0.86
    H1000’s







    H2000’s 6.7 (-21 to 35)

-16 (-36 to 4.7)

0.63 (-0.94 to 2.2)

0.82 (-0.93 to 2.6)

    H3000’s 1.3 (-24 to 26)

1.3 (-17 to 20)

0.44 (-0.95 to 1.8)

0.15 (-1.4 to 1.7)

mean_APexc_mean * group_char
0.95
0.99

0.20 0.39
0.61 0.71
0.86 0.86
    mean_APexc_mean * H2000’s -14 (-566 to 538)

336 (-66 to 738)

-14 (-45 to 16)

-8.6 (-41 to 23)

    mean_APexc_mean * H3000’s 69 (-415 to 553)

-16 (-367 to 335)

-8.7 (-35 to 18)

-4.7 (-32 to 23)

subj_char.sd__(Intercept) 2.2 (NA to NA)

4.1 (NA to NA)

0.49 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -9.7 (-28 to 8.9) 0.30 0.78 1.5 (-13 to 16) 0.84 0.89 -0.13 (-1.3 to 1.0) 0.83 0.90 0.90 (-0.46 to 2.3) 0.19 0.77
mean_MLexc_COV 0.32 (-0.86 to 1.5) 0.60 0.78 0.06 (-0.85 to 0.97) 0.89 0.89 0.00 (-0.07 to 0.08) 0.90 0.90 0.01 (-0.08 to 0.09) 0.88 0.88
group_char
0.66 0.78
0.71 0.89
0.61 0.90
0.49 0.88
    H1000’s







    H2000’s 4.4 (-22 to 31)

8.4 (-12 to 29)

-0.78 (-2.3 to 0.78)

1.1 (-0.76 to 2.9)

    H3000’s 11 (-13 to 36)

2.8 (-16 to 22)

-0.27 (-1.7 to 1.2)

0.34 (-1.4 to 2.1)

mean_MLexc_COV * group_char
0.78 0.78
0.56 0.89
0.61 0.90
0.77 0.88
    mean_MLexc_COV * H2000’s 0.19 (-1.5 to 1.9)

-0.68 (-2.0 to 0.60)

0.05 (-0.05 to 0.15)

-0.04 (-0.15 to 0.07)

    mean_MLexc_COV * H3000’s -0.38 (-2.0 to 1.2)

-0.19 (-1.4 to 1.0)

0.02 (-0.07 to 0.11)

-0.03 (-0.13 to 0.08)

subj_char.sd__(Intercept) 2.5 (NA to NA)

4.6 (NA to NA)

0.50 (NA to NA)

0.89 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -4.6 (-23 to 14) 0.62 0.96 -1.3 (-15 to 12) 0.86
0.99
-0.04 (-1.1 to 0.99) 0.94 0.96 1.2 (0.06 to 2.4) 0.039 0.16
mean_MLexc_mean -5.2 (-220 to 209) 0.96 0.96 46 (-112 to 205) 0.57
0.99
-0.29 (-12 to 12) 0.96 0.96 -2.9 (-16 to 9.8) 0.65 0.79
group_char
0.57 0.96
0.99
0.99

0.87 0.96
0.54 0.79
    H1000’s







    H2000’s 13 (-11 to 37)

-1.6 (-20 to 16)

0.14 (-1.2 to 1.5)

0.38 (-1.2 to 1.9)

    H3000’s 6.2 (-17 to 29)

-0.86 (-18 to 16)

0.34 (-0.97 to 1.7)

-0.41 (-1.9 to 1.1)

mean_MLexc_mean * group_char
0.84 0.96
0.99
0.99

0.89 0.96
0.79 0.79
    mean_MLexc_mean * H2000’s -67 (-343 to 209)

-3.5 (-207 to 200)

-2.2 (-17 to 13)

1.3 (-15 to 17)

    mean_MLexc_mean * H3000’s -6.1 (-263 to 251)

4.4 (-186 to 195)

-3.5 (-18 to 11)

4.7 (-11 to 20)

subj_char.sd__(Intercept) 2.8 (NA to NA)

4.2 (NA to NA)

0.48 (NA to NA)

0.87 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -11 (-28 to 4.9) 0.17 0.54 3.0 (-8.6 to 15) 0.61 0.81 -0.43 (-1.3 to 0.43) 0.33 0.35 1.4 (0.44 to 2.4) 0.004 0.017
mean_StepDur 6.7 (-9.5 to 23) 0.42 0.54 -0.61 (-12 to 11) 0.92 0.92 0.40 (-0.43 to 1.2) 0.35 0.35 -0.45 (-1.3 to 0.40) 0.30 0.60
group_char
0.27 0.54
0.11 0.22
0.13 0.27
0.99
0.99
    H1000’s







    H2000’s 22 (-5.1 to 49)

-21 (-40 to -1.4)

1.4 (-0.02 to 2.9)

0.09 (-1.5 to 1.7)

    H3000’s 12 (-16 to 40)

-6.4 (-27 to 14)

0.88 (-0.61 to 2.4)

-0.04 (-1.7 to 1.6)

mean_StepDur * group_char
0.54 0.54
0.090 0.22
0.067 0.27
0.88
0.99
    mean_StepDur * H2000’s -18 (-49 to 14)

25 (2.6 to 48)

-1.9 (-3.5 to -0.22)

0.40 (-1.3 to 2.1)

    mean_StepDur * H3000’s -7.0 (-43 to 29)

9.1 (-16 to 35)

-1.1 (-3.0 to 0.75)

-0.12 (-2.1 to 1.8)

subj_char.sd__(Intercept) 2.6 (NA to NA)

3.9 (NA to NA)

0.51 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.0 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.9 (-21 to 6.7) 0.32 0.94 0.93 (-9.1 to 11) 0.86 0.86 -0.06 (-0.82 to 0.69) 0.87
0.99
1.1 (0.23 to 2.0) 0.013 0.054
mean_UDexc_COV 0.16 (-0.84 to 1.2) 0.76 0.94 0.12 (-0.59 to 0.84) 0.73 0.86 0.00 (-0.05 to 0.05)
0.99
0.99
-0.01 (-0.06 to 0.05) 0.76 0.76
group_char
0.60 0.94
0.49 0.86
0.51
0.99

0.40 0.76
    H1000’s







    H2000’s 10 (-12 to 33)

-9.7 (-26 to 6.6)

0.64 (-0.59 to 1.9)

0.78 (-0.61 to 2.2)

    H3000’s 8.4 (-12 to 29)

-2.0 (-17 to 13)

-0.05 (-1.2 to 1.1)

-0.17 (-1.5 to 1.1)

mean_UDexc_COV * group_char
0.94 0.94
0.60 0.86
0.38
0.99

0.75 0.76
    mean_UDexc_COV * H2000’s -0.24 (-1.8 to 1.3)

0.57 (-0.55 to 1.7)

-0.05 (-0.13 to 0.03)

-0.02 (-0.11 to 0.06)

    mean_UDexc_COV * H3000’s -0.22 (-1.7 to 1.2)

0.14 (-0.91 to 1.2)

0.00 (-0.07 to 0.08)

0.01 (-0.07 to 0.09)

subj_char.sd__(Intercept) 2.1 (NA to NA)

4.4 (NA to NA)

0.48 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.5 (-19 to 14) 0.77 0.95 5.3 (-6.7 to 17) 0.39 0.92 -0.25 (-1.1 to 0.64) 0.58 0.64 0.98 (-0.03 to 2.0) 0.057 0.23
mean_UDexc_mean -105 (-745 to 534) 0.75 0.95 -118 (-579 to 343) 0.62 0.92 8.0 (-26 to 42) 0.64 0.64 0.56 (-34 to 35) 0.98 0.98
group_char
0.95 0.95
0.92 0.92
0.34 0.64
0.69 0.98
    H1000’s







    H2000’s 1.9 (-22 to 26)

3.3 (-14 to 21)

-0.66 (-2.0 to 0.63)

0.59 (-0.88 to 2.0)

    H3000’s 3.6 (-19 to 26)

0.43 (-16 to 17)

0.27 (-0.97 to 1.5)

0.05 (-1.4 to 1.5)

mean_UDexc_mean * group_char
0.89 0.95
0.77 0.92
0.30 0.64
0.98 0.98
    mean_UDexc_mean * H2000’s 224 (-709 to 1,157)

-216 (-889 to 457)

26 (-23 to 75)

-4.8 (-56 to 46)

    mean_UDexc_mean * H3000’s 83 (-763 to 928)

-8.0 (-625 to 609)

-10 (-56 to 35)

-2.5 (-51 to 46)

subj_char.sd__(Intercept) 2.2 (NA to NA)

4.2 (NA to NA)

0.45 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -10 (-24 to 3.7) 0.15 0.56 2.9 (-7.1 to 13) 0.57 0.76 -0.38 (-1.1 to 0.37) 0.32 0.33 1.3 (0.48 to 2.2) 0.002 0.009
mean_StanceDur 4.0 (-5.8 to 14) 0.42 0.56 -0.34 (-7.3 to 6.6) 0.92 0.92 0.25 (-0.25 to 0.74) 0.33 0.33 -0.27 (-0.78 to 0.24) 0.30 0.60
group_char
0.28 0.56
0.13 0.27
0.17 0.33
0.92 0.94
    H1000’s







    H2000’s 18 (-4.8 to 40)

-17 (-33 to -0.28)

1.1 (-0.08 to 2.4)

0.26 (-1.1 to 1.6)

    H3000’s 11 (-13 to 34)

-4.5 (-21 to 12)

0.66 (-0.58 to 1.9)

-0.03 (-1.4 to 1.4)

mean_StanceDur * group_char
0.63 0.63
0.11 0.27
0.074 0.30
0.94 0.94
    mean_StanceDur * H2000’s -9.2 (-28 to 9.7)

14 (0.89 to 28)

-1.1 (-2.1 to -0.12)

0.14 (-0.87 to 1.2)

    mean_StanceDur * H3000’s -3.9 (-25 to 17)

4.7 (-10 to 20)

-0.60 (-1.7 to 0.49)

-0.08 (-1.2 to 1.1)

subj_char.sd__(Intercept) 2.4 (NA to NA)

3.8 (NA to NA)

0.50 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.0 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -11 (-27 to 4.9) 0.17 0.54 3.0 (-8.6 to 15) 0.61 0.81 -0.43 (-1.3 to 0.43) 0.33 0.34 1.4 (0.44 to 2.4) 0.004 0.017
mean_GaitCycleDur 3.4 (-4.7 to 11) 0.42 0.54 -0.30 (-6.0 to 5.4) 0.92 0.92 0.20 (-0.21 to 0.61) 0.34 0.34 -0.22 (-0.65 to 0.20) 0.30 0.60
group_char
0.27 0.54
0.11 0.22
0.13 0.27
0.99 0.99
    H1000’s







    H2000’s 22 (-5.0 to 49)

-21 (-40 to -1.4)

1.4 (-0.02 to 2.9)

0.09 (-1.5 to 1.7)

    H3000’s 12 (-16 to 40)

-6.4 (-26 to 14)

0.88 (-0.61 to 2.4)

-0.04 (-1.7 to 1.6)

mean_GaitCycleDur * group_char
0.54 0.54
0.090 0.22
0.066 0.27
0.88 0.99
    mean_GaitCycleDur * H2000’s -8.8 (-25 to 7.0)

13 (1.3 to 24)

-0.93 (-1.7 to -0.11)

0.20 (-0.66 to 1.1)

    mean_GaitCycleDur * H3000’s -3.5 (-21 to 14)

4.5 (-8.2 to 17)

-0.55 (-1.5 to 0.37)

-0.06 (-1.0 to 0.91)

subj_char.sd__(Intercept) 2.6 (NA to NA)

3.9 (NA to NA)

0.51 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.0 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -3.8 (-17 to 9.6) 0.58 0.91 3.5 (-6.3 to 13) 0.48 0.87 -0.05 (-0.78 to 0.69) 0.90 0.96 0.92 (0.08 to 1.8) 0.032 0.13
mean_PeakUpDownVel_mean -5.2 (-55 to 45) 0.84 0.91 -4.4 (-40 to 32) 0.81 0.87 -0.06 (-2.7 to 2.5) 0.96 0.96 0.29 (-2.4 to 2.9) 0.83 0.94
group_char
0.91 0.91
0.87 0.87
0.45 0.89
0.65 0.94
    H1000’s







    H2000’s 1.6 (-18 to 21)

3.5 (-11 to 18)

-0.57 (-1.6 to 0.52)

0.58 (-0.67 to 1.8)

    H3000’s 4.1 (-15 to 23)

2.9 (-11 to 17)

0.09 (-0.95 to 1.1)

0.16 (-1.0 to 1.4)

mean_PeakUpDownVel_mean * group_char
0.81 0.91
0.74 0.87
0.40 0.89
0.94 0.94
    mean_PeakUpDownVel_mean * H2000’s 23 (-49 to 94)

-20 (-71 to 31)

2.0 (-1.7 to 5.7)

-0.45 (-4.3 to 3.4)

    mean_PeakUpDownVel_mean * H3000’s 6.0 (-61 to 73)

-10 (-59 to 38)

-0.29 (-3.8 to 3.3)

-0.66 (-4.4 to 3.0)

subj_char.sd__(Intercept) 2.3 (NA to NA)

4.0 (NA to NA)

0.47 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 9.0 (-14 to 32) 0.44 0.83 0.62 (-14 to 15) 0.93 0.97 -0.55 (-1.7 to 0.65) 0.37 0.49 0.89 (-0.17 to 2.0) 0.10 0.14
mean_APexc_COV -0.33 (-1.6 to 0.97) 0.62 0.83 0.01 (-0.80 to 0.83) 0.97 0.97 0.02 (-0.04 to 0.09) 0.52 0.52 -0.01 (-0.07 to 0.04) 0.65 0.65
group_char
0.86 0.86
0.79 0.97
0.28 0.49
0.10 0.14
    H1000’s







    H2000’s 5.7 (-34 to 45)

6.0 (-20 to 32)

0.69 (-1.4 to 2.8)

-1.7 (-3.7 to 0.20)

    H3000’s -5.0 (-36 to 26)

-3.1 (-24 to 17)

1.4 (-0.31 to 3.1)

0.34 (-1.2 to 1.9)

mean_APexc_COV * group_char
0.39 0.83
0.97 0.97
0.37 0.49
0.007 0.030
    mean_APexc_COV * H2000’s -0.67 (-2.6 to 1.3)

-0.10 (-1.3 to 1.1)

-0.03 (-0.13 to 0.07)

0.13 (0.05 to 0.22)

    mean_APexc_COV * H3000’s 0.45 (-1.1 to 2.0)

0.03 (-0.93 to 1.0)

-0.06 (-0.14 to 0.02)

0.03 (-0.04 to 0.09)

subj_char.sd__(Intercept) 7.9 (NA to NA)

8.7 (NA to NA)

0.76 (NA to NA)

1.0 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.87 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.9 (-14 to 22) 0.68 0.90 1.2 (-11 to 13) 0.85 0.95 -0.36 (-1.3 to 0.62) 0.47 0.63 0.46 (-0.43 to 1.4) 0.31 0.42
mean_APexc_mean -7.9 (-335 to 320) 0.96 0.96 -6.3 (-212 to 199) 0.95 0.95 3.2 (-13 to 20) 0.70 0.70 4.1 (-9.8 to 18) 0.56 0.56
group_char
0.003 0.006
0.86 0.95
0.015 0.030
0.020 0.039
    H1000’s







    H2000’s 51 (20 to 81)

-4.5 (-25 to 16)

2.4 (0.73 to 4.0)

-0.37 (-1.9 to 1.1)

    H3000’s 7.8 (-16 to 32)

0.87 (-16 to 17)

0.43 (-0.89 to 1.8)

1.4 (0.20 to 2.7)

mean_APexc_mean * group_char
<0.001 <0.001
0.47 0.95
0.009 0.030
0.006 0.026
    mean_APexc_mean * H2000’s -1,476 (-2,124 to -829)

198 (-220 to 616)

-52 (-86 to -18)

37 (8.0 to 65)

    mean_APexc_mean * H3000’s -98 (-572 to 376)

-71 (-383 to 240)

-6.6 (-32 to 18)

-12 (-33 to 9.8)

subj_char.sd__(Intercept) 4.5 (NA to NA)

8.6 (NA to NA)

0.71 (NA to NA)

0.94 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -7.3 (-26 to 11) 0.45 0.45 0.14 (-13 to 13) 0.98 0.98 0.49 (-0.60 to 1.6) 0.38 0.75 0.96 (-0.09 to 2.0) 0.073 0.15
mean_MLexc_COV 0.74 (-0.48 to 2.0) 0.23 0.45 0.05 (-0.79 to 0.88) 0.91 0.98 -0.05 (-0.12 to 0.02) 0.18 0.73 -0.02 (-0.08 to 0.04) 0.54 0.54
group_char
0.45 0.45
0.26 0.98
0.96 0.98
0.31 0.41
    H1000’s







    H2000’s 19 (-11 to 49)

5.1 (-15 to 25)

0.24 (-1.4 to 1.9)

-0.26 (-1.8 to 1.3)

    H3000’s 11 (-16 to 37)

-10 (-28 to 7.7)

0.11 (-1.4 to 1.6)

0.81 (-0.60 to 2.2)

mean_MLexc_COV * group_char
0.12 0.45
0.49 0.98
0.98 0.98
0.060 0.15
    mean_MLexc_COV * H2000’s -2.2 (-4.3 to -0.09)

-0.09 (-1.4 to 1.2)

-0.01 (-0.12 to 0.10)

0.10 (0.01 to 0.20)

    mean_MLexc_COV * H3000’s -0.48 (-2.2 to 1.3)

0.58 (-0.57 to 1.7)

0.00 (-0.09 to 0.09)

0.01 (-0.08 to 0.09)

subj_char.sd__(Intercept) 7.4 (NA to NA)

8.9 (NA to NA)

0.75 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 11 (-5.9 to 29) 0.20 0.67 1.5 (-9.6 to 13) 0.79 0.89 -0.72 (-1.7 to 0.23) 0.14 0.28 0.24 (-0.65 to 1.1) 0.59 0.74
mean_MLexc_mean -98 (-297 to 101) 0.33 0.67 -8.6 (-131 to 113) 0.89 0.89 6.6 (-3.8 to 17) 0.21 0.28 5.3 (-3.7 to 14) 0.25 0.49
group_char
0.68 0.91
0.18 0.36
0.27 0.28
0.075 0.30
    H1000’s







    H2000’s -4.8 (-30 to 21)

1.4 (-15 to 18)

1.1 (-0.25 to 2.5)

1.3 (-0.04 to 2.6)

    H3000’s 5.6 (-17 to 28)

12 (-2.3 to 27)

0.48 (-0.78 to 1.7)

1.3 (0.06 to 2.5)

mean_MLexc_mean * group_char
0.91 0.91
0.017 0.067
0.28 0.28
0.74 0.74
    mean_MLexc_mean * H2000’s -58 (-336 to 220)

29 (-137 to 194)

-11 (-25 to 2.8)

-2.2 (-14 to 9.9)

    mean_MLexc_mean * H3000’s -14 (-263 to 235)

-166 (-320 to -12)

-4.6 (-18 to 8.5)

-4.5 (-16 to 7.0)

subj_char.sd__(Intercept) 7.4 (NA to NA)

8.8 (NA to NA)

0.75 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.4 (-13 to 20) 0.69 0.91 1.6 (-8.8 to 12) 0.76 0.87 -0.32 (-1.2 to 0.55) 0.48 0.63 0.29 (-0.52 to 1.1) 0.49 0.49
mean_StepDur 0.06 (-17 to 17)
0.99
0.99
-0.87 (-11 to 9.2) 0.87 0.87 0.14 (-0.69 to 0.98) 0.74 0.74 0.43 (-0.26 to 1.1) 0.22 0.43
group_char
0.13 0.25
0.34 0.67
0.087 0.17
0.077 0.31
    H1000’s







    H2000’s 28 (-3.0 to 58)

-1.7 (-21 to 17)

1.6 (0.00 to 3.2)

0.67 (-0.78 to 2.1)

    H3000’s 21 (-5.7 to 48)

12 (-5.6 to 29)

-0.23 (-1.7 to 1.2)

1.5 (0.20 to 2.8)

mean_StepDur * group_char
0.018 0.071
0.10 0.39
0.078 0.17
0.32 0.43
    mean_StepDur * H2000’s -51 (-88 to -14)

7.2 (-15 to 29)

-1.9 (-3.7 to -0.02)

0.68 (-0.85 to 2.2)

    mean_StepDur * H3000’s -25 (-60 to 8.6)

-20 (-41 to 0.90)

0.56 (-1.2 to 2.3)

-0.76 (-2.2 to 0.72)

subj_char.sd__(Intercept) 6.6 (NA to NA)

8.4 (NA to NA)

0.72 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.0 (-7.8 to 20) 0.40 0.53 1.1 (-8.0 to 10) 0.81 0.95 -0.38 (-1.1 to 0.37) 0.32 0.53 0.41 (-0.31 to 1.1) 0.27 0.30
mean_UDexc_COV -0.20 (-1.2 to 0.78) 0.69 0.69 -0.02 (-0.61 to 0.57) 0.95 0.95 0.02 (-0.03 to 0.06) 0.53 0.53 0.02 (-0.02 to 0.06) 0.30 0.30
group_char
0.37 0.53
0.84 0.95
0.49 0.53
0.065 0.20
    H1000’s







    H2000’s 6.4 (-16 to 29)

2.4 (-13 to 17)

0.71 (-0.54 to 2.0)

0.50 (-0.68 to 1.7)

    H3000’s 15 (-6.0 to 36)

4.2 (-9.8 to 18)

0.04 (-1.1 to 1.2)

1.3 (0.21 to 2.4)

mean_UDexc_COV * group_char
0.25 0.53
0.48 0.95
0.51 0.53
0.10 0.20
    mean_UDexc_COV * H2000’s -1.3 (-2.9 to 0.31)

0.11 (-0.85 to 1.1)

-0.04 (-0.12 to 0.04)

0.05 (-0.02 to 0.11)

    mean_UDexc_COV * H3000’s -0.83 (-2.3 to 0.64)

-0.46 (-1.4 to 0.45)

0.01 (-0.07 to 0.08)

-0.03 (-0.09 to 0.03)

subj_char.sd__(Intercept) 7.0 (NA to NA)

8.8 (NA to NA)

0.75 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.4 (-16 to 18) 0.87 0.87 -0.08 (-11 to 11) 0.99 0.99 0.10 (-0.80 to 1.0) 0.83 0.83 1.1 (0.27 to 1.9) 0.010 0.039
mean_UDexc_mean 91 (-608 to 789) 0.80 0.87 41 (-385 to 468) 0.85 0.99 -13 (-48 to 22) 0.48 0.64 -19 (-48 to 10) 0.21 0.22
group_char
0.23 0.66
0.31 0.99
0.47 0.64
0.11 0.22
    H1000’s







    H2000’s -21 (-46 to 3.9)

4.9 (-11 to 21)

-0.25 (-1.6 to 1.1)

1.3 (0.06 to 2.6)

    H3000’s -14 (-37 to 9.0)

-7.3 (-22 to 7.9)

0.54 (-0.71 to 1.8)

0.34 (-0.83 to 1.5)

mean_UDexc_mean * group_char
0.33 0.66
0.64 0.99
0.34 0.64
0.22 0.22
    mean_UDexc_mean * H2000’s 424 (-546 to 1,394)

-47 (-640 to 547)

19 (-30 to 67)

-7.3 (-48 to 33)

    mean_UDexc_mean * H3000’s 679 (-215 to 1,573)

195 (-358 to 747)

-14 (-60 to 31)

24 (-14 to 62)

subj_char.sd__(Intercept) 7.6 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.99 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.3 (-11 to 17) 0.65 0.86 1.5 (-7.6 to 11) 0.74 0.86 -0.28 (-1.0 to 0.47) 0.47 0.62 0.38 (-0.35 to 1.1) 0.31 0.37
mean_StanceDur 0.16 (-10 to 10) 0.97 0.97 -0.54 (-6.6 to 5.5) 0.86 0.86 0.08 (-0.42 to 0.58) 0.77 0.77 0.24 (-0.17 to 0.66) 0.25 0.37
group_char
0.20 0.40
0.48 0.86
0.14 0.28
0.064 0.26
    H1000’s







    H2000’s 18 (-7.8 to 43)

0.10 (-16 to 16)

1.2 (-0.14 to 2.5)

0.77 (-0.49 to 2.0)

    H3000’s 18 (-4.5 to 41)

8.5 (-6.1 to 23)

-0.16 (-1.4 to 1.1)

1.3 (0.21 to 2.5)

mean_StanceDur * group_char
0.030 0.12
0.13 0.51
0.11 0.28
0.37 0.37
    mean_StanceDur * H2000’s -28 (-50 to -5.9)

3.6 (-9.6 to 17)

-1.0 (-2.1 to 0.09)

0.39 (-0.52 to 1.3)

    mean_StanceDur * H3000’s -16 (-36 to 5.2)

-12 (-24 to 1.1)

0.33 (-0.72 to 1.4)

-0.41 (-1.3 to 0.47)

subj_char.sd__(Intercept) 6.9 (NA to NA)

8.5 (NA to NA)

0.73 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.4 (-13 to 20) 0.68 0.91 1.6 (-8.8 to 12) 0.76 0.87 -0.32 (-1.2 to 0.55) 0.47 0.63 0.29 (-0.52 to 1.1) 0.49 0.49
mean_GaitCycleDur 0.02 (-8.4 to 8.5)
0.99
0.99
-0.43 (-5.5 to 4.6) 0.87 0.87 0.07 (-0.34 to 0.49) 0.73 0.73 0.21 (-0.13 to 0.56) 0.23 0.43
group_char
0.12 0.25
0.34 0.67
0.085 0.17
0.078 0.31
    H1000’s







    H2000’s 28 (-2.8 to 58)

-1.7 (-21 to 17)

1.6 (0.00 to 3.2)

0.66 (-0.78 to 2.1)

    H3000’s 21 (-5.6 to 48)

12 (-5.6 to 29)

-0.23 (-1.7 to 1.2)

1.5 (0.20 to 2.8)

mean_GaitCycleDur * group_char
0.017 0.068
0.10 0.39
0.076 0.17
0.32 0.43
    mean_GaitCycleDur * H2000’s -26 (-44 to -7.2)

3.6 (-7.5 to 15)

-0.93 (-1.8 to -0.02)

0.34 (-0.42 to 1.1)

    mean_GaitCycleDur * H3000’s -13 (-30 to 4.3)

-10 (-21 to 0.45)

0.28 (-0.59 to 1.1)

-0.38 (-1.1 to 0.36)

subj_char.sd__(Intercept) 6.6 (NA to NA)

8.4 (NA to NA)

0.72 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 0.13 (-13 to 13) 0.98 0.98 0.26 (-8.4 to 8.9) 0.95 0.95 0.11 (-0.61 to 0.82) 0.77 0.77 0.93 (0.24 to 1.6) 0.009 0.035
mean_PeakUpDownVel_mean 15 (-35 to 64) 0.57 0.76 2.6 (-28 to 33) 0.87 0.95 -1.3 (-3.7 to 1.2) 0.31 0.42 -1.1 (-3.2 to 0.95) 0.29 0.29
group_char
0.15 0.58
0.094 0.38
0.26 0.42
0.050 0.10
    H1000’s







    H2000’s -20 (-41 to 0.00)

6.8 (-6.7 to 20)

-0.43 (-1.5 to 0.68)

1.4 (0.27 to 2.5)

    H3000’s -9.6 (-28 to 8.7)

-7.9 (-20 to 4.2)

0.49 (-0.52 to 1.5)

0.50 (-0.49 to 1.5)

mean_PeakUpDownVel_mean * group_char
0.38 0.75
0.26 0.53
0.10 0.39
0.19 0.25
    mean_PeakUpDownVel_mean * H2000’s 35 (-36 to 107)

-12 (-55 to 32)

2.5 (-1.0 to 6.0)

-0.88 (-3.8 to 2.1)

    mean_PeakUpDownVel_mean * H3000’s 45 (-19 to 109)

20 (-19 to 60)

-1.1 (-4.3 to 2.1)

1.6 (-1.1 to 4.3)

subj_char.sd__(Intercept) 7.0 (NA to NA)

8.5 (NA to NA)

0.73 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.8 (-65 to 73) 0.91 0.97 4.0 (-7.3 to 15) 0.49 0.75 -0.41 (-1.4 to 0.59) 0.42 0.88 0.63 (-0.62 to 1.9) 0.32 0.89
mean_APexc_COV -0.09 (-4.3 to 4.1) 0.97 0.97 -0.11 (-0.80 to 0.58) 0.75 0.75 0.01 (-0.05 to 0.07) 0.73 0.88 0.00 (-0.08 to 0.07) 0.90 0.90
group_char
0.27 0.94
0.67 0.75
0.72 0.88
0.45 0.89
    H1000’s







    H2000’s -10 (-115 to 95)

3.3 (-14 to 20)

-0.59 (-2.1 to 0.96)

0.70 (-1.3 to 2.7)

    H3000’s -75 (-172 to 23)

-4.4 (-20 to 11)

-0.46 (-1.9 to 0.97)

1.2 (-0.66 to 3.0)

mean_APexc_COV * group_char
0.47 0.94
0.49 0.75
0.88 0.88
0.74 0.90
    mean_APexc_COV * H2000’s 0.07 (-5.4 to 5.5)

-0.23 (-1.1 to 0.66)

0.02 (-0.06 to 0.10)

0.03 (-0.07 to 0.13)

    mean_APexc_COV * H3000’s 2.3 (-2.6 to 7.2)

0.19 (-0.61 to 0.98)

0.00 (-0.07 to 0.07)

0.00 (-0.09 to 0.08)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 4.3 (-59 to 68) 0.89 0.95 2.7 (-7.5 to 13) 0.61 0.81 -0.24 (-1.1 to 0.63) 0.59
0.99
0.66 (-0.42 to 1.7) 0.23 0.83
mean_APexc_mean -37 (-1,167 to 1,093) 0.95 0.95 -9.0 (-191 to 173) 0.92 0.92 -0.04 (-15 to 15)
0.99
0.99
-2.0 (-20 to 16) 0.83 0.83
group_char
0.70 0.95
0.046 0.16
0.93
0.99

0.50 0.83
    H1000’s







    H2000’s -7.4 (-101 to 86)

-15 (-30 to -0.15)

-0.09 (-1.4 to 1.2)

0.95 (-0.69 to 2.6)

    H3000’s -32 (-111 to 47)

1.1 (-12 to 14)

-0.21 (-1.3 to 0.92)

0.63 (-0.82 to 2.1)

mean_APexc_mean * group_char
0.80 0.95
0.079 0.16
0.99
0.99

0.74 0.83
    mean_APexc_mean * H2000’s -58 (-1,951 to 1,836)

289 (-16 to 593)

-1.1 (-27 to 25)

7.5 (-24 to 39)

    mean_APexc_mean * H3000’s 469 (-1,119 to 2,057)

-47 (-303 to 208)

-1.2 (-24 to 21)

11 (-17 to 38)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 80 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.7 (-56 to 60) 0.95 0.98 3.7 (-5.7 to 13) 0.44 0.84 -0.31 (-1.2 to 0.57) 0.49 0.87 0.05 (-1.1 to 1.2) 0.94 0.94
mean_MLexc_COV 0.04 (-3.9 to 4.0) 0.98 0.98 -0.11 (-0.75 to 0.53) 0.74 0.84 0.00 (-0.05 to 0.06) 0.87 0.87 0.04 (-0.04 to 0.11) 0.34 0.68
group_char
0.57 0.98
0.84 0.84
0.80 0.87
0.022 0.090
    H1000’s







    H2000’s -14 (-91 to 64)

-0.89 (-14 to 12)

0.14 (-1.0 to 1.3)

2.0 (0.57 to 3.5)

    H3000’s -46 (-132 to 41)

-4.1 (-18 to 10)

0.42 (-0.85 to 1.7)

1.5 (-0.10 to 3.1)

mean_MLexc_COV * group_char
0.71 0.98
0.73 0.84
0.54 0.87
0.53 0.70
    mean_MLexc_COV * H2000’s 0.30 (-5.0 to 5.6)

-0.12 (-0.98 to 0.74)

-0.02 (-0.10 to 0.06)

-0.05 (-0.15 to 0.04)

    mean_MLexc_COV * H3000’s 2.2 (-3.5 to 8.0)

0.24 (-0.69 to 1.2)

-0.05 (-0.13 to 0.04)

-0.03 (-0.13 to 0.07)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 80 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.0 (-52 to 57) 0.92 0.98 3.1 (-5.7 to 12) 0.49 0.66 -0.27 (-1.0 to 0.50) 0.49 0.94 0.89 (-0.09 to 1.9) 0.074 0.29
mean_MLexc_mean -8.2 (-645 to 628) 0.98 0.98 -11 (-114 to 92) 0.83 0.83 0.34 (-8.3 to 9.0) 0.94 0.94 -4.2 (-15 to 6.3) 0.43 0.58
group_char
0.81 0.98
0.22 0.66
0.48 0.94
0.35 0.58
    H1000’s







    H2000’s -8.5 (-80 to 63)

-8.8 (-20 to 2.6)

-0.42 (-1.4 to 0.60)

0.96 (-0.34 to 2.3)

    H3000’s -22 (-93 to 48)

-1.0 (-12 to 10)

-0.63 (-1.7 to 0.40)

0.62 (-0.71 to 2.0)

mean_MLexc_mean * group_char
0.92 0.98
0.40 0.66
0.73 0.94
0.73 0.73
    mean_MLexc_mean * H2000’s -10 (-794 to 774)

71 (-56 to 197)

3.0 (-7.6 to 14)

4.1 (-8.9 to 17)

    mean_MLexc_mean * H3000’s 120 (-693 to 933)

5.4 (-126 to 137)

4.6 (-6.7 to 16)

5.5 (-8.4 to 19)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.55 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 80 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.0 (-50 to 52) 0.97 0.97 1.8 (-6.5 to 10) 0.67 0.89 -0.04 (-0.73 to 0.66) 0.92 0.92 0.69 (-0.18 to 1.6) 0.12 0.47
mean_StepDur 1.4 (-52 to 55) 0.96 0.97 0.42 (-8.2 to 9.1) 0.92 0.92 -0.23 (-0.91 to 0.46) 0.51 0.69 -0.16 (-0.96 to 0.65) 0.70 0.70
group_char
0.59 0.97
0.18 0.56
0.18 0.56
0.52 0.70
    H1000’s







    H2000’s 0.28 (-84 to 85)

-11 (-25 to 2.3)

-0.53 (-1.7 to 0.62)

0.83 (-0.60 to 2.3)

    H3000’s -45 (-135 to 46)

2.2 (-13 to 17)

-1.2 (-2.5 to 0.08)

0.35 (-1.3 to 2.0)

mean_StepDur * group_char
0.67 0.97
0.28 0.56
0.28 0.56
0.53 0.70
    mean_StepDur * H2000’s -13 (-114 to 88)

12 (-4.5 to 28)

0.47 (-0.84 to 1.8)

0.58 (-0.98 to 2.1)

    mean_StepDur * H3000’s 50 (-74 to 174)

-4.1 (-24 to 16)

1.4 (-0.36 to 3.1)

1.1 (-1.1 to 3.2)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 80 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -0.11 (-44 to 43)
0.99
0.99
3.4 (-3.7 to 10) 0.35 0.86 -0.15 (-0.76 to 0.45) 0.62 0.74 0.61 (-0.18 to 1.4) 0.13 0.27
mean_UDexc_COV 0.19 (-3.0 to 3.4) 0.91
0.99
-0.10 (-0.62 to 0.43) 0.72 0.86 -0.01 (-0.05 to 0.03) 0.74 0.74 0.00 (-0.06 to 0.05) 0.85 0.85
group_char
0.33 0.94
0.62 0.86
0.031 0.12
0.13 0.27
    H1000’s







    H2000’s -11 (-76 to 54)

-5.2 (-16 to 5.4)

-0.74 (-1.6 to 0.16)

1.2 (0.01 to 2.4)

    H3000’s -51 (-120 to 17)

-1.3 (-13 to 9.9)

-1.2 (-2.2 to -0.30)

0.73 (-0.51 to 2.0)

mean_UDexc_COV * group_char
0.47 0.94
0.86 0.86
0.076 0.15
0.81 0.85
    mean_UDexc_COV * H2000’s 0.11 (-4.5 to 4.7)

0.21 (-0.55 to 0.97)

0.05 (-0.01 to 0.11)

0.01 (-0.06 to 0.08)

    mean_UDexc_COV * H3000’s 2.7 (-2.1 to 7.4)

0.06 (-0.71 to 0.84)

0.07 (0.01 to 0.13)

0.02 (-0.05 to 0.10)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.51 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

0.99 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.3 (-46 to 50) 0.93
0.99
2.3 (-5.7 to 10) 0.57 0.80 -0.25 (-0.91 to 0.42) 0.47 0.62 0.43 (-0.43 to 1.3) 0.33 0.65
mean_UDexc_mean 0.79 (-1,903 to 1,905)
0.99
0.99
-3.6 (-318 to 311) 0.98 0.98 0.20 (-25 to 25) 0.99 0.99 5.1 (-25 to 35) 0.74 0.74
group_char
0.16 0.32
0.39 0.80
0.32 0.62
0.015 0.062
    H1000’s







    H2000’s -6.4 (-72 to 60)

-6.3 (-17 to 4.6)

0.33 (-0.59 to 1.3)

1.7 (0.49 to 2.9)

    H3000’s 53 (-15 to 122)

0.57 (-11 to 12)

0.74 (-0.22 to 1.7)

1.3 (0.08 to 2.6)

mean_UDexc_mean * group_char
0.076 0.30
0.60 0.80
0.090 0.36
0.72 0.74
    mean_UDexc_mean * H2000’s -129 (-2,710 to 2,453)

157 (-269 to 583)

-20 (-54 to 15)

-17 (-58 to 24)

    mean_UDexc_mean * H3000’s -2,584 (-5,172 to 2.9)

-45 (-472 to 383)

-39 (-74 to -4.1)

-11 (-53 to 32)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.48 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 78 (NA to NA)

13 (NA to NA)

0.99 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.2 (-42 to 44) 0.96 0.96 1.9 (-5.0 to 8.8) 0.59 0.79 -0.05 (-0.64 to 0.53) 0.86 0.86 0.68 (-0.08 to 1.4) 0.077 0.31
mean_StanceDur 0.92 (-31 to 33) 0.95 0.96 0.25 (-4.9 to 5.4) 0.92 0.92 -0.15 (-0.56 to 0.25) 0.46 0.62 -0.11 (-0.58 to 0.37) 0.66 0.66
group_char
0.61 0.96
0.15 0.51
0.081 0.27
0.30 0.59
    H1000’s







    H2000’s -2.8 (-73 to 67)

-9.6 (-21 to 1.7)

-0.46 (-1.4 to 0.49)

0.96 (-0.26 to 2.2)

    H3000’s -37 (-114 to 39)

2.4 (-10 to 15)

-1.2 (-2.3 to -0.15)

0.49 (-0.87 to 1.8)

mean_StanceDur * group_char
0.71 0.96
0.25 0.51
0.14 0.27
0.56 0.66
    mean_StanceDur * H2000’s -6.4 (-67 to 54)

7.1 (-2.7 to 17)

0.29 (-0.49 to 1.1)

0.30 (-0.62 to 1.2)

    mean_StanceDur * H3000’s 28 (-47 to 104)

-3.3 (-16 to 9.0)

1.0 (0.00 to 2.0)

0.62 (-0.61 to 1.9)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 80 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.0 (-50 to 52) 0.97 0.97 1.8 (-6.5 to 10) 0.67 0.89 -0.04 (-0.73 to 0.66) 0.92 0.92 0.69 (-0.18 to 1.6) 0.12 0.47
mean_GaitCycleDur 0.69 (-26 to 27) 0.96 0.97 0.21 (-4.1 to 4.5) 0.92 0.92 -0.11 (-0.45 to 0.23) 0.51 0.68 -0.08 (-0.48 to 0.32) 0.70 0.70
group_char
0.59 0.97
0.18 0.56
0.18 0.55
0.52 0.70
    H1000’s







    H2000’s 0.30 (-84 to 85)

-11 (-25 to 2.3)

-0.53 (-1.7 to 0.62)

0.83 (-0.60 to 2.3)

    H3000’s -45 (-135 to 46)

2.2 (-12 to 17)

-1.2 (-2.5 to 0.08)

0.34 (-1.3 to 2.0)

mean_GaitCycleDur * group_char
0.66 0.97
0.28 0.56
0.28 0.55
0.53 0.70
    mean_GaitCycleDur * H2000’s -6.3 (-57 to 44)

5.9 (-2.3 to 14)

0.24 (-0.42 to 0.89)

0.29 (-0.49 to 1.1)

    mean_GaitCycleDur * H3000’s 25 (-37 to 87)

-2.0 (-12 to 8.0)

0.68 (-0.18 to 1.5)

0.53 (-0.53 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 80 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.2 (-36 to 42) 0.87 0.96 2.1 (-4.4 to 8.6) 0.53 0.97 -0.33 (-0.88 to 0.21) 0.23 0.42 0.50 (-0.22 to 1.2) 0.17 0.35
mean_PeakUpDownVel_mean -4.0 (-154 to 146) 0.96 0.96 0.43 (-24 to 25) 0.97 0.97 0.38 (-1.6 to 2.3) 0.70 0.70 0.21 (-2.1 to 2.5) 0.86 0.86
group_char
0.10 0.19
0.62 0.97
0.32 0.42
0.007 0.028
    H1000’s







    H2000’s -8.3 (-64 to 47)

-4.1 (-13 to 5.1)

0.26 (-0.53 to 1.0)

1.6 (0.60 to 2.7)

    H3000’s 51 (-6.3 to 108)

-0.19 (-9.7 to 9.3)

0.63 (-0.18 to 1.4)

1.1 (0.02 to 2.2)

mean_PeakUpDownVel_mean * group_char
0.036 0.14
0.88 0.97
0.061 0.24
0.63 0.84
    mean_PeakUpDownVel_mean * H2000’s -4.5 (-209 to 200)

6.3 (-28 to 40)

-1.6 (-4.2 to 1.1)

-1.4 (-4.6 to 1.8)

    mean_PeakUpDownVel_mean * H3000’s -224 (-426 to -23)

-1.5 (-35 to 32)

-3.2 (-5.8 to -0.55)

-0.13 (-3.3 to 3.1)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.50 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 78 (NA to NA)

13 (NA to NA)

0.99 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 23 (-15 to 61) 0.23 0.46 -2.0 (-15 to 12) 0.77 0.89 -0.45 (-1.5 to 0.63) 0.42 0.89 0.53 (-0.68 to 1.7) 0.39 0.39
mean_APexc_COV -1.4 (-3.7 to 0.88) 0.23 0.46 0.06 (-0.77 to 0.90) 0.89 0.89 0.00 (-0.06 to 0.07) 0.89 0.89 0.04 (-0.02 to 0.11) 0.22 0.29
group_char
0.61 0.61
0.47 0.89
0.76 0.89
0.047 0.19
    H1000’s







    H2000’s -30 (-88 to 29)

12 (-8.5 to 33)

-0.59 (-2.3 to 1.1)

1.9 (-0.13 to 3.9)

    H3000’s -14 (-65 to 38)

1.8 (-16 to 20)

-0.44 (-1.9 to 1.1)

2.0 (0.28 to 3.7)

mean_APexc_COV * group_char
0.58 0.61
0.64 0.89
0.88 0.89
0.19 0.29
    mean_APexc_COV * H2000’s 1.5 (-1.5 to 4.5)

-0.41 (-1.5 to 0.66)

0.02 (-0.07 to 0.11)

-0.06 (-0.15 to 0.03)

    mean_APexc_COV * H3000’s 1.2 (-1.5 to 3.9)

-0.04 (-1.0 to 0.92)

0.01 (-0.07 to 0.08)

-0.07 (-0.15 to 0.01)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.2 (-25 to 38) 0.70 0.89 -7.5 (-19 to 4.0) 0.20 0.33 -0.53 (-1.4 to 0.35) 0.24 0.82 1.1 (0.11 to 2.1) 0.030 0.12
mean_APexc_mean -104 (-645 to 437) 0.71 0.89 120 (-84 to 323) 0.25 0.33 2.9 (-12 to 18) 0.70 0.82 1.2 (-13 to 15) 0.87 0.87
group_char
0.75 0.89
0.25 0.33
0.82 0.82
0.35 0.70
    H1000’s







    H2000’s -6.2 (-51 to 38)

14 (-2.5 to 30)

-0.41 (-1.7 to 0.86)

0.94 (-0.53 to 2.4)

    H3000’s 9.0 (-31 to 49)

8.0 (-6.5 to 23)

-0.22 (-1.4 to 0.93)

0.88 (-0.49 to 2.3)

mean_APexc_mean * group_char
0.89 0.89
0.41 0.41
0.80 0.82
0.81 0.87
    mean_APexc_mean * H2000’s 7.9 (-820 to 836)

-204 (-511 to 103)

7.6 (-16 to 31)

-1.5 (-23 to 20)

    mean_APexc_mean * H3000’s -166 (-947 to 614)

-123 (-408 to 161)

1.5 (-21 to 24)

-7.0 (-29 to 15)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 17 (-13 to 46) 0.26 0.35 3.1 (-7.2 to 13) 0.56 0.86 0.06 (-0.81 to 0.93) 0.90 0.90 0.60 (-0.49 to 1.7) 0.28 0.28
mean_MLexc_COV -1.1 (-3.0 to 0.77) 0.25 0.35 -0.27 (-0.93 to 0.38) 0.41 0.86 -0.03 (-0.08 to 0.03) 0.30 0.40 0.04 (-0.02 to 0.10) 0.20 0.27
group_char
0.26 0.35
0.86 0.86
0.12 0.34
0.063 0.25
    H1000’s







    H2000’s -29 (-69 to 11)

0.89 (-13 to 15)

-0.40 (-1.6 to 0.78)

1.5 (-0.01 to 3.0)

    H3000’s -1.7 (-43 to 40)

-3.0 (-18 to 12)

-1.2 (-2.5 to -0.03)

1.6 (0.16 to 3.1)

mean_MLexc_COV * group_char
0.40 0.40
0.84 0.86
0.17 0.34
0.20 0.27
    mean_MLexc_COV * H2000’s 1.7 (-0.91 to 4.2)

0.15 (-0.77 to 1.1)

0.02 (-0.05 to 0.10)

-0.04 (-0.12 to 0.04)

    mean_MLexc_COV * H3000’s 0.35 (-2.3 to 3.0)

0.29 (-0.66 to 1.2)

0.07 (-0.01 to 0.15)

-0.07 (-0.15 to 0.01)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.94 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 4.0 (-24 to 32) 0.78 0.97 -5.6 (-15 to 4.2) 0.26 0.44 -0.65 (-1.4 to 0.15) 0.11 0.44 1.2 (0.21 to 2.1) 0.018 0.070
mean_MLexc_mean -43 (-367 to 280) 0.79 0.97 58 (-59 to 175) 0.33 0.44 3.4 (-5.7 to 13) 0.46 0.55 -0.09 (-9.2 to 9.0) 0.98 0.98
group_char
0.97 0.97
0.32 0.44
0.55 0.55
0.27 0.54
    H1000’s







    H2000’s -3.9 (-42 to 34)

10 (-3.2 to 24)

-0.37 (-1.5 to 0.71)

1.1 (-0.24 to 2.5)

    H3000’s 0.16 (-35 to 36)

6.0 (-6.5 to 19)

0.17 (-0.85 to 1.2)

0.64 (-0.66 to 1.9)

mean_MLexc_mean * group_char
0.96 0.97
0.53 0.53
0.34 0.55
0.87 0.98
    mean_MLexc_mean * H2000’s -4.4 (-408 to 399)

-84 (-232 to 63)

2.4 (-8.9 to 14)

-2.6 (-14 to 8.4)

    mean_MLexc_mean * H3000’s 44 (-360 to 447)

-59 (-205 to 86)

-4.6 (-16 to 6.8)

-0.74 (-12 to 11)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 40 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.2 (-24 to 27) 0.93 0.96 -2.9 (-12 to 6.5) 0.55 0.75 -0.49 (-1.2 to 0.22) 0.18 0.71 1.1 (0.26 to 2.0) 0.011 0.045
mean_StepDur -0.70 (-26 to 25) 0.96 0.96 2.1 (-7.6 to 12) 0.67 0.75 0.13 (-0.56 to 0.82) 0.72 0.76 0.05 (-0.57 to 0.67) 0.87 0.87
group_char
0.52 0.96
0.54 0.75
0.72 0.76
0.26 0.52
    H1000’s







    H2000’s -5.0 (-49 to 39)

9.3 (-7.1 to 26)

-0.42 (-1.6 to 0.81)

1.2 (-0.25 to 2.6)

    H3000’s 20 (-21 to 61)

3.7 (-11 to 19)

-0.40 (-1.6 to 0.77)

0.62 (-0.75 to 2.0)

mean_StepDur * group_char
0.63 0.96
0.75 0.75
0.76 0.76
0.83 0.87
    mean_StepDur * H2000’s -0.22 (-51 to 50)

-7.4 (-27 to 12)

0.47 (-0.92 to 1.9)

-0.38 (-1.6 to 0.88)

    mean_StepDur * H3000’s -24 (-76 to 27)

-2.7 (-22 to 16)

0.35 (-1.1 to 1.8)

-0.04 (-1.4 to 1.3)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -3.0 (-26 to 20) 0.79 0.85 -1.5 (-9.9 to 7.0) 0.73
0.99
-0.54 (-1.2 to 0.11) 0.11 0.42 1.1 (0.30 to 2.0) 0.007 0.029
mean_UDexc_COV 0.29 (-1.4 to 1.9) 0.73 0.85 0.04 (-0.59 to 0.66) 0.91
0.99
0.01 (-0.03 to 0.06) 0.57
0.99
0.00 (-0.04 to 0.04) 0.87 0.87
group_char
0.63 0.85
0.86
0.99

0.88
0.99

0.18 0.37
    H1000’s







    H2000’s -4.7 (-38 to 28)

3.5 (-8.7 to 16)

-0.12 (-1.1 to 0.82)

1.1 (-0.13 to 2.3)

    H3000’s 12 (-22 to 45)

1.9 (-11 to 14)

-0.25 (-1.2 to 0.71)

0.80 (-0.39 to 2.0)

mean_UDexc_COV * group_char
0.85 0.85
0.99
0.99

0.99
0.99

0.80 0.87
    mean_UDexc_COV * H2000’s -0.05 (-2.3 to 2.2)

-0.02 (-0.88 to 0.85)

0.00 (-0.06 to 0.07)

-0.02 (-0.08 to 0.04)

    mean_UDexc_COV * H3000’s -0.61 (-2.9 to 1.7)

-0.05 (-0.92 to 0.83)

0.00 (-0.06 to 0.07)

-0.02 (-0.08 to 0.04)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 40 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.96 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.8 (-22 to 30) 0.77 0.92 -0.68 (-10 to 8.9) 0.89 0.98 -0.20 (-0.94 to 0.54) 0.59 0.62 1.4 (0.49 to 2.3) 0.002 0.010
mean_UDexc_mean -138 (-1,159 to 883) 0.79 0.92 -14 (-397 to 369) 0.94 0.98 -7.2 (-35 to 21) 0.62 0.62 -9.2 (-35 to 17) 0.49 0.80
group_char
0.72 0.92
0.98 0.98
0.43 0.62
0.80 0.80
    H1000’s







    H2000’s -8.3 (-46 to 30)

-0.41 (-14 to 14)

0.18 (-0.90 to 1.3)

0.44 (-0.88 to 1.8)

    H3000’s 7.1 (-29 to 43)

0.81 (-12 to 14)

-0.48 (-1.5 to 0.54)

0.29 (-0.96 to 1.5)

mean_UDexc_mean * group_char
0.92 0.92
0.84 0.98
0.54 0.62
0.63 0.80
    mean_UDexc_mean * H2000’s 135 (-1,290 to 1,560)

145 (-388 to 679)

-9.5 (-49 to 30)

17 (-19 to 54)

    mean_UDexc_mean * H3000’s -140 (-1,518 to 1,237)

21 (-493 to 535)

12 (-26 to 50)

12 (-24 to 48)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 40 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 0.53 (-21 to 22) 0.96
0.99
-2.5 (-10 to 5.5) 0.54 0.69 -0.44 (-1.1 to 0.17) 0.16 0.62 1.1 (0.32 to 1.9) 0.006 0.025
mean_StanceDur 0.04 (-15 to 15)
0.99
0.99
1.2 (-4.6 to 7.0) 0.69 0.69 0.06 (-0.36 to 0.47) 0.79 0.79 0.04 (-0.33 to 0.41) 0.83 0.85
group_char
0.48
0.99

0.45 0.69
0.72 0.79
0.22 0.45
    H1000’s







    H2000’s -5.5 (-42 to 31)

8.7 (-4.7 to 22)

-0.33 (-1.4 to 0.69)

1.1 (-0.17 to 2.4)

    H3000’s 17 (-17 to 52)

3.1 (-9.6 to 16)

-0.36 (-1.3 to 0.63)

0.63 (-0.59 to 1.9)

mean_StanceDur * group_char
0.62
0.99

0.69 0.69
0.79 0.79
0.85 0.85
    mean_StanceDur * H2000’s 0.40 (-29 to 30)

-5.0 (-16 to 6.4)

0.26 (-0.56 to 1.1)

-0.22 (-0.96 to 0.52)

    mean_StanceDur * H3000’s -15 (-46 to 16)

-1.6 (-13 to 10)

0.20 (-0.66 to 1.1)

-0.05 (-0.84 to 0.75)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.2 (-24 to 27) 0.92 0.96 -2.9 (-12 to 6.5) 0.55 0.75 -0.49 (-1.2 to 0.22) 0.18 0.71 1.1 (0.26 to 2.0) 0.011 0.044
mean_GaitCycleDur -0.35 (-13 to 12) 0.96 0.96 1.0 (-3.8 to 5.9) 0.67 0.75 0.06 (-0.28 to 0.41) 0.72 0.76 0.03 (-0.28 to 0.34) 0.87 0.87
group_char
0.52 0.96
0.54 0.75
0.72 0.76
0.26 0.52
    H1000’s







    H2000’s -5.0 (-49 to 39)

9.2 (-7.1 to 26)

-0.42 (-1.6 to 0.81)

1.2 (-0.24 to 2.6)

    H3000’s 20 (-21 to 61)

3.7 (-11 to 19)

-0.40 (-1.6 to 0.76)

0.61 (-0.75 to 2.0)

mean_GaitCycleDur * group_char
0.63 0.96
0.75 0.75
0.76 0.76
0.83 0.87
    mean_GaitCycleDur * H2000’s -0.13 (-25 to 25)

-3.7 (-13 to 5.9)

0.23 (-0.46 to 0.92)

-0.19 (-0.82 to 0.44)

    mean_GaitCycleDur * H3000’s -12 (-38 to 13)

-1.4 (-11 to 8.2)

0.18 (-0.54 to 0.89)

-0.02 (-0.69 to 0.66)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.8 (-19 to 23) 0.87 0.98 -1.2 (-8.9 to 6.6) 0.77 0.97 -0.14 (-0.74 to 0.46) 0.64 0.64 1.3 (0.48 to 2.1) 0.002 0.007
mean_PeakUpDownVel_mean -5.0 (-83 to 73) 0.90 0.98 0.73 (-29 to 31) 0.96 0.97 -0.97 (-3.1 to 1.2) 0.37 0.64 -0.44 (-2.4 to 1.5) 0.65 0.81
group_char
0.78 0.98
0.97 0.97
0.39 0.64
0.52 0.81
    H1000’s







    H2000’s -7.0 (-38 to 24)

1.2 (-10 to 13)

0.05 (-0.84 to 0.94)

0.64 (-0.54 to 1.8)

    H3000’s 4.0 (-26 to 34)

1.2 (-9.6 to 12)

-0.49 (-1.3 to 0.35)

0.50 (-0.62 to 1.6)

mean_PeakUpDownVel_mean * group_char
0.98 0.98
0.92 0.97
0.51 0.64
0.81 0.81
    mean_PeakUpDownVel_mean * H2000’s 7.9 (-102 to 118)

7.6 (-34 to 49)

-0.37 (-3.4 to 2.6)

0.88 (-1.8 to 3.6)

    mean_PeakUpDownVel_mean * H3000’s -0.98 (-105 to 103)

0.39 (-39 to 40)

1.2 (-1.7 to 4.1)

0.34 (-2.3 to 3.0)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 40 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.96 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 14 (-18 to 45) 0.39 0.53 1.0 (-4.6 to 6.7) 0.73 0.86 -0.58 (-1.6 to 0.49) 0.29 0.49 1.0 (-0.20 to 2.3) 0.10 0.26
mean_APexc_COV -0.76 (-2.7 to 1.2) 0.45 0.53 -0.03 (-0.38 to 0.32) 0.86 0.86 0.02 (-0.05 to 0.08) 0.56 0.56 -0.01 (-0.08 to 0.07) 0.86 0.90
group_char
0.36 0.53
0.47 0.86
0.30 0.49
0.13 0.26
    H1000’s







    H2000’s -26 (-76 to 23)

-3.2 (-12 to 5.7)

-0.07 (-1.7 to 1.6)

2.0 (0.05 to 4.0)

    H3000’s -29 (-71 to 13)

2.2 (-5.4 to 9.9)

1.0 (-0.46 to 2.5)

0.72 (-1.0 to 2.4)

mean_APexc_COV * group_char
0.53 0.53
0.85 0.86
0.36 0.49
0.90 0.90
    mean_APexc_COV * H2000’s 0.95 (-1.7 to 3.6)

0.09 (-0.37 to 0.56)

-0.01 (-0.09 to 0.08)

-0.02 (-0.12 to 0.07)

    mean_APexc_COV * H3000’s 1.3 (-0.94 to 3.5)

-0.01 (-0.40 to 0.39)

-0.04 (-0.11 to 0.03)

-0.02 (-0.10 to 0.07)

subj_char.sd__(Intercept) 0.00 (NA to NA)

2.4 (NA to NA)

0.79 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 31 (NA to NA)

4.9 (NA to NA)

0.81 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.3 (-29 to 24) 0.86 0.86 0.65 (-3.7 to 5.0) 0.77 0.95 0.01 (-0.79 to 0.82) 0.98 0.98 0.83 (-0.12 to 1.8) 0.086 0.34
mean_APexc_mean 80 (-382 to 542) 0.74 0.86 -2.2 (-77 to 72) 0.95 0.95 -5.4 (-18 to 7.5) 0.41 0.84 1.9 (-12 to 16) 0.79 0.79
group_char
0.48 0.86
0.045 0.18
0.65 0.87
0.20 0.40
    H1000’s







    H2000’s 20 (-18 to 59)

-0.99 (-7.6 to 5.6)

-0.31 (-1.6 to 0.93)

1.4 (-0.12 to 2.8)

    H3000’s 1.0 (-32 to 34)

5.7 (0.04 to 11)

-0.51 (-1.6 to 0.57)

0.50 (-0.80 to 1.8)

mean_APexc_mean * group_char
0.18 0.74
0.16 0.32
0.42 0.84
0.71 0.79
    mean_APexc_mean * H2000’s -653 (-1,392 to 85)

-8.1 (-132 to 115)

4.4 (-18 to 26)

3.4 (-21 to 28)

    mean_APexc_mean * H3000’s -82 (-710 to 547)

-97 (-202 to 9.4)

13 (-6.3 to 32)

-6.8 (-28 to 15)

subj_char.sd__(Intercept) 1.7 (NA to NA)

2.5 (NA to NA)

0.76 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 31 (NA to NA)

4.8 (NA to NA)

0.82 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.6 (-18 to 21) 0.87 0.96 0.51 (-3.3 to 4.3) 0.79
0.99
-0.31 (-1.1 to 0.47) 0.44 0.94 1.1 (0.10 to 2.0) 0.031 0.062
mean_MLexc_COV 0.03 (-1.2 to 1.3) 0.96 0.96 0.00 (-0.24 to 0.24)
0.99
0.99
0.00 (-0.05 to 0.05) 0.94 0.94 -0.01 (-0.06 to 0.05) 0.77 0.77
group_char
0.042 0.17
0.45 0.91
0.94 0.94
0.009 0.036
    H1000’s







    H2000’s -41 (-74 to -8.3)

-1.3 (-7.2 to 4.6)

0.20 (-0.98 to 1.4)

2.0 (0.53 to 3.4)

    H3000’s -6.6 (-39 to 26)

-3.8 (-9.6 to 2.1)

0.00 (-1.2 to 1.2)

-0.04 (-1.4 to 1.4)

mean_MLexc_COV * group_char
0.12 0.23
0.10 0.41
0.79 0.94
0.48 0.64
    mean_MLexc_COV * H2000’s 2.3 (0.06 to 4.5)

0.00 (-0.39 to 0.39)

-0.02 (-0.09 to 0.05)

-0.04 (-0.12 to 0.05)

    mean_MLexc_COV * H3000’s 0.22 (-1.9 to 2.3)

0.37 (0.00 to 0.75)

0.01 (-0.06 to 0.08)

0.02 (-0.06 to 0.10)

subj_char.sd__(Intercept) 4.8 (NA to NA)

2.5 (NA to NA)

0.77 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 31 (NA to NA)

4.8 (NA to NA)

0.82 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.1 (-23 to 19) 0.85 0.85 0.65 (-3.1 to 4.4) 0.74 0.94 -0.11 (-0.84 to 0.62) 0.76 0.86 0.81 (-0.05 to 1.7) 0.066 0.26
mean_MLexc_mean 54 (-205 to 314) 0.68 0.85 -1.7 (-47 to 44) 0.94 0.94 -2.3 (-10 to 5.8) 0.58 0.86 1.6 (-7.4 to 11) 0.73 0.73
group_char
0.091 0.18
0.18 0.72
0.84 0.86
0.21 0.41
    H1000’s







    H2000’s 27 (-3.3 to 57)

-1.6 (-7.1 to 3.9)

-0.30 (-1.4 to 0.78)

1.2 (-0.12 to 2.5)

    H3000’s -3.2 (-31 to 25)

3.2 (-1.9 to 8.4)

-0.04 (-1.1 to 0.97)

0.45 (-0.77 to 1.7)

mean_MLexc_mean * group_char
0.011 0.045
0.70 0.94
0.86 0.86
0.47 0.63
    mean_MLexc_mean * H2000’s -418 (-759 to -77)

3.4 (-56 to 63)

2.9 (-7.7 to 14)

3.3 (-8.6 to 15)

    mean_MLexc_mean * H3000’s -10 (-331 to 311)

-17 (-74 to 40)

1.8 (-8.4 to 12)

-3.2 (-15 to 8.2)

subj_char.sd__(Intercept) 3.7 (NA to NA)

2.5 (NA to NA)

0.77 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 30 (NA to NA)

4.9 (NA to NA)

0.82 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -3.8 (-23 to 16) 0.70 0.70 0.67 (-2.7 to 4.0) 0.70 0.92 -0.19 (-0.83 to 0.45) 0.56 0.92 0.87 (0.10 to 1.6) 0.027 0.11
mean_StepDur 6.3 (-14 to 26) 0.53 0.70 -0.16 (-3.4 to 3.1) 0.92 0.92 -0.10 (-0.66 to 0.45) 0.71 0.92 0.08 (-0.53 to 0.68) 0.80 0.80
group_char
0.003 0.006
0.036 0.14
0.92 0.92
0.68 0.80
    H1000’s







    H2000’s 63 (26 to 100)

-0.50 (-6.9 to 5.9)

-0.23 (-1.4 to 0.97)

0.63 (-0.77 to 2.0)

    H3000’s 4.8 (-28 to 38)

7.1 (1.3 to 13)

-0.16 (-1.3 to 0.94)

0.15 (-1.2 to 1.4)

mean_StepDur * group_char
<0.001 <0.001
0.092 0.18
0.86 0.92
0.28 0.55
    mean_StepDur * H2000’s -95 (-140 to -50)

-1.1 (-8.5 to 6.3)

0.19 (-1.1 to 1.5)

1.1 (-0.26 to 2.6)

    mean_StepDur * H3000’s -9.8 (-52 to 32)

-8.0 (-15 to -0.81)

0.34 (-0.94 to 1.6)

0.09 (-1.3 to 1.5)

subj_char.sd__(Intercept) 0.00 (NA to NA)

2.6 (NA to NA)

0.77 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 30 (NA to NA)

4.8 (NA to NA)

0.82 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.5 (-14 to 21) 0.69 0.86 0.61 (-2.4 to 3.6) 0.69 0.93 -0.32 (-0.92 to 0.27) 0.28 0.50 0.92 (0.19 to 1.6) 0.013 0.026
mean_UDexc_COV -0.12 (-1.4 to 1.2) 0.86 0.86 -0.01 (-0.22 to 0.21) 0.95 0.95 0.00 (-0.03 to 0.04) 0.87 0.87 0.00 (-0.04 to 0.04) 0.94 0.94
group_char
0.74 0.86
0.14 0.55
0.37 0.50
0.006 0.024
    H1000’s







    H2000’s 2.0 (-25 to 29)

-1.4 (-6.1 to 3.3)

-0.37 (-1.3 to 0.56)

1.7 (0.54 to 2.8)

    H3000’s -9.8 (-39 to 20)

4.0 (-1.1 to 9.1)

0.39 (-0.59 to 1.4)

-0.09 (-1.3 to 1.1)

mean_UDexc_COV * group_char
0.42 0.86
0.57 0.93
0.36 0.50
0.62 0.83
    mean_UDexc_COV * H2000’s -0.93 (-2.9 to 1.0)

0.01 (-0.31 to 0.33)

0.02 (-0.03 to 0.08)

-0.01 (-0.08 to 0.05)

    mean_UDexc_COV * H3000’s 0.47 (-1.6 to 2.6)

-0.16 (-0.51 to 0.18)

-0.02 (-0.08 to 0.04)

0.02 (-0.05 to 0.09)

subj_char.sd__(Intercept) 3.6 (NA to NA)

2.4 (NA to NA)

0.78 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 31 (NA to NA)

4.9 (NA to NA)

0.81 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 13 (-7.5 to 33) 0.22 0.27 0.44 (-3.0 to 3.9) 0.80 0.96 -0.35 (-1.0 to 0.30) 0.30 0.59 0.90 (0.11 to 1.7) 0.025 0.055
mean_UDexc_mean -444 (-1,233 to 344) 0.27 0.27 3.4 (-126 to 133) 0.96 0.96 2.6 (-19 to 25) 0.82 0.82 1.4 (-23 to 26) 0.91 0.91
group_char
0.075 0.27
0.84 0.96
0.46 0.62
0.028 0.055
    H1000’s







    H2000’s -36 (-66 to -4.9)

-1.3 (-6.6 to 4.0)

0.45 (-0.55 to 1.5)

1.7 (0.45 to 2.9)

    H3000’s -14 (-44 to 16)

0.30 (-4.9 to 5.5)

-0.21 (-1.2 to 0.78)

0.61 (-0.59 to 1.8)

mean_UDexc_mean * group_char
0.22 0.27
0.81 0.96
0.17 0.59
0.66 0.88
    mean_UDexc_mean * H2000’s 1,038 (-137 to 2,214)

-2.7 (-196 to 191)

-21 (-54 to 12)

-7.4 (-44 to 29)

    mean_UDexc_mean * H3000’s 425 (-734 to 1,584)

56 (-138 to 249)

12 (-21 to 45)

-17 (-54 to 20)

subj_char.sd__(Intercept) 4.5 (NA to NA)

2.5 (NA to NA)

0.76 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 31 (NA to NA)

4.9 (NA to NA)

0.81 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.6 (-19 to 14) 0.76 0.76 0.65 (-2.2 to 3.6) 0.66 0.88 -0.20 (-0.77 to 0.37) 0.49 0.96 0.87 (0.17 to 1.6) 0.015 0.059
mean_StanceDur 3.7 (-8.3 to 16) 0.55 0.73 -0.10 (-2.0 to 1.8) 0.92 0.92 -0.07 (-0.40 to 0.27) 0.70 0.96 0.05 (-0.31 to 0.42) 0.77 0.77
group_char
0.001 0.003
0.026 0.11
0.96 0.96
0.44 0.58
    H1000’s







    H2000’s 54 (23 to 84)

-0.77 (-6.1 to 4.5)

-0.15 (-1.2 to 0.87)

0.80 (-0.43 to 2.0)

    H3000’s 1.4 (-26 to 29)

6.1 (1.2 to 11)

-0.07 (-1.0 to 0.89)

0.18 (-0.97 to 1.3)

mean_StanceDur * group_char
<0.001 <0.001
0.087 0.17
0.93 0.96
0.26 0.52
    mean_StanceDur * H2000’s -61 (-88 to -35)

-0.58 (-4.9 to 3.8)

0.07 (-0.69 to 0.82)

0.69 (-0.14 to 1.5)

    mean_StanceDur * H3000’s -3.9 (-29 to 21)

-4.8 (-9.2 to -0.54)

0.15 (-0.61 to 0.91)

0.03 (-0.80 to 0.86)

subj_char.sd__(Intercept) 0.00 (NA to NA)

2.6 (NA to NA)

0.77 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 30 (NA to NA)

4.8 (NA to NA)

0.82 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -3.8 (-23 to 16) 0.71 0.71 0.67 (-2.7 to 4.0) 0.70 0.92 -0.19 (-0.83 to 0.45) 0.56 0.92 0.87 (0.10 to 1.6) 0.027 0.11
mean_GaitCycleDur 3.2 (-6.8 to 13) 0.54 0.71 -0.08 (-1.7 to 1.5) 0.92 0.92 -0.05 (-0.33 to 0.23) 0.72 0.92 0.04 (-0.26 to 0.34) 0.81 0.81
group_char
0.003 0.006
0.034 0.14
0.92 0.92
0.67 0.81
    H1000’s







    H2000’s 63 (26 to 100)

-0.51 (-6.9 to 5.9)

-0.23 (-1.4 to 0.97)

0.63 (-0.76 to 2.0)

    H3000’s 4.8 (-28 to 38)

7.2 (1.4 to 13)

-0.17 (-1.3 to 0.94)

0.14 (-1.2 to 1.4)

mean_GaitCycleDur * group_char
<0.001 <0.001
0.088 0.18
0.85 0.92
0.28 0.57
    mean_GaitCycleDur * H2000’s -47 (-70 to -25)

-0.56 (-4.2 to 3.1)

0.09 (-0.55 to 0.74)

0.57 (-0.14 to 1.3)

    mean_GaitCycleDur * H3000’s -4.9 (-26 to 16)

-4.0 (-7.6 to -0.44)

0.17 (-0.47 to 0.81)

0.05 (-0.66 to 0.75)

subj_char.sd__(Intercept) 0.00 (NA to NA)

2.6 (NA to NA)

0.77 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 30 (NA to NA)

4.8 (NA to NA)

0.82 (NA to NA)

0.89 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 13
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 8.6 (-7.6 to 25) 0.30 0.38 0.43 (-2.4 to 3.2) 0.76 0.93 -0.36 (-0.91 to 0.18) 0.19 0.49 0.99 (0.31 to 1.7) 0.004 0.017
mean_PeakUpDownVel_mean -27 (-89 to 34) 0.38 0.38 0.42 (-9.5 to 10) 0.93 0.93 0.33 (-1.3 to 2.0) 0.69 0.69 -0.24 (-2.1 to 1.6) 0.80 0.87
group_char
0.048 0.19
0.74 0.93
0.64 0.69
0.015 0.030
    H1000’s







    H2000’s -33 (-59 to -6.7)

-1.6 (-6.2 to 2.9)

0.38 (-0.51 to 1.3)

1.6 (0.50 to 2.7)

    H3000’s -10 (-35 to 14)

-0.04 (-4.3 to 4.2)

-0.03 (-0.87 to 0.81)

0.39 (-0.65 to 1.4)

mean_PeakUpDownVel_mean * group_char
0.18 0.35
0.65 0.93
0.24 0.49
0.87 0.87
    mean_PeakUpDownVel_mean * H2000’s 89 (-5.3 to 184)

1.1 (-14 to 16)

-1.7 (-4.3 to 0.84)

-0.40 (-3.3 to 2.5)

    mean_PeakUpDownVel_mean * H3000’s 29 (-59 to 116)

6.4 (-7.9 to 21)

0.43 (-2.0 to 2.9)

-0.74 (-3.4 to 2.0)

subj_char.sd__(Intercept) 4.7 (NA to NA)

2.4 (NA to NA)

0.77 (NA to NA)

1.1 (NA to NA)

Residual.sd__Observation 31 (NA to NA)

4.9 (NA to NA)

0.82 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

LME EEG ~ 1+kin+group

Changes in theta_avg_power for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -4.5 (-25 to 16) 0.67 0.67 0.03 (-0.77 to 0.83) 0.94 0.94 -0.74 (-1.2 to -0.24) 0.004 0.011 1.1 (0.44 to 1.9) 0.002 0.005
mean_APexc_COV 0.47 (-0.66 to 1.6) 0.41 0.62 0.01 (-0.03 to 0.06) 0.52 0.77 0.00 (-0.02 to 0.03) 0.86 0.86 0.00 (-0.03 to 0.03) 0.91 0.91
group_char
0.14 0.41
0.43 0.77
0.47 0.70
0.12 0.19
    H1000’s







    H2000’s -16 (-33 to 0.19)

-0.24 (-0.88 to 0.40)

0.29 (-0.23 to 0.80)

0.85 (-0.04 to 1.7)

    H3000’s -13 (-31 to 4.7)

0.17 (-0.52 to 0.86)

0.27 (-0.25 to 0.80)

0.70 (-0.19 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 5.4 (-18 to 29) 0.65 0.83 1.0 (0.10 to 1.9) 0.030 0.089 -0.66 (-1.2 to -0.13) 0.014 0.043 0.91 (0.18 to 1.6) 0.015 0.045
mean_APexc_mean -42 (-434 to 350) 0.83 0.83 -14 (-29 to 1.6) 0.080 0.12 -0.82 (-8.6 to 7.0) 0.84 0.84 4.9 (-3.8 to 14) 0.27 0.27
group_char
0.20 0.59
0.44 0.44
0.41 0.62
0.074 0.11
    H1000’s







    H2000’s -14 (-29 to 1.6)

-0.29 (-0.89 to 0.31)

0.29 (-0.21 to 0.79)

0.91 (0.03 to 1.8)

    H3000’s -9.5 (-25 to 6.3)

0.10 (-0.51 to 0.71)

0.28 (-0.21 to 0.77)

0.78 (-0.08 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -14 (-34 to 5.8) 0.16 0.21 -0.02 (-0.79 to 0.76) 0.97 0.97 -0.69 (-1.2 to -0.20) 0.006 0.018 1.5 (0.77 to 2.2) <0.001 <0.001
mean_MLexc_COV 1.2 (-0.02 to 2.4) 0.054 0.16 0.02 (-0.03 to 0.07) 0.42 0.63 0.00 (-0.03 to 0.03) 0.93 0.93 -0.02 (-0.05 to 0.01) 0.19 0.19
group_char
0.21 0.21
0.34 0.63
0.37 0.55
0.10 0.15
    H1000’s







    H2000’s -13 (-28 to 2.0)

-0.15 (-0.73 to 0.44)

0.30 (-0.19 to 0.79)

0.85 (-0.02 to 1.7)

    H3000’s -8.6 (-23 to 6.0)

0.31 (-0.26 to 0.88)

0.29 (-0.19 to 0.77)

0.71 (-0.14 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 14 (-4.2 to 31) 0.13 0.23 0.63 (-0.07 to 1.3) 0.077 0.23 -0.80 (-1.2 to -0.37) <0.001 <0.001 0.91 (0.26 to 1.6) 0.006 0.018
mean_MLexc_mean -129 (-315 to 56) 0.17 0.23 -4.4 (-12 to 2.8) 0.23 0.34 1.2 (-2.6 to 4.9) 0.54 0.54 3.3 (-0.85 to 7.4) 0.12 0.12
group_char
0.23 0.23
0.37 0.37
0.38 0.54
0.11 0.12
    H1000’s







    H2000’s -12 (-28 to 2.5)

-0.12 (-0.71 to 0.46)

0.29 (-0.20 to 0.78)

0.84 (-0.03 to 1.7)

    H3000’s -8.7 (-23 to 5.9)

0.31 (-0.26 to 0.88)

0.29 (-0.19 to 0.77)

0.71 (-0.14 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.73 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

0.99 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 7.8 (-24 to 40) 0.64 0.76 0.82 (-0.10 to 1.7) 0.080 0.24 -0.53 (-1.1 to 0.02) 0.057 0.17 0.78 (0.07 to 1.5) 0.031 0.078
mean_StepDur -5.1 (-37 to 27) 0.76 0.76 -0.60 (-1.5 to 0.31) 0.20 0.30 -0.20 (-0.67 to 0.27) 0.40 0.60 0.43 (-0.05 to 0.91) 0.078 0.078
group_char
0.34 0.76
0.44 0.44
0.60 0.60
0.061 0.078
    H1000’s







    H2000’s -14 (-35 to 6.8)

-0.25 (-0.85 to 0.35)

0.27 (-0.26 to 0.80)

0.93 (0.04 to 1.8)

    H3000’s -0.50 (-22 to 21)

0.16 (-0.45 to 0.76)

0.16 (-0.36 to 0.69)

0.86 (-0.01 to 1.7)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.79 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 72 (NA to NA)

2.1 (NA to NA)

1.0 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 9.0 (-8.0 to 26) 0.30 0.41 0.49 (-0.17 to 1.1) 0.15 0.42 -0.71 (-1.1 to -0.30) <0.001 0.002 1.1 (0.46 to 1.7) <0.001 0.002
mean_UDexc_COV -0.47 (-1.6 to 0.64) 0.41 0.41 -0.02 (-0.06 to 0.03) 0.42 0.42 0.00 (-0.02 to 0.02)
0.99
0.99
0.01 (-0.02 to 0.03) 0.53 0.53
group_char
0.22 0.41
0.32 0.42
0.37 0.55
0.10 0.16
    H1000’s







    H2000’s -13 (-28 to 2.1)

-0.14 (-0.72 to 0.45)

0.30 (-0.19 to 0.79)

0.86 (-0.02 to 1.7)

    H3000’s -8.3 (-23 to 6.4)

0.32 (-0.25 to 0.89)

0.29 (-0.19 to 0.77)

0.70 (-0.15 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.74 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -11 (-29 to 7.7) 0.26 0.26 0.02 (-0.70 to 0.74) 0.95 0.95 -0.85 (-1.3 to -0.41) <0.001 <0.001 1.5 (0.89 to 2.2) <0.001 <0.001
mean_UDexc_mean 579 (-85 to 1,242) 0.087 0.25 10 (-16 to 36) 0.44 0.65 5.9 (-6.9 to 19) 0.37 0.38 -15 (-29 to -1.2) 0.034 0.051
group_char
0.17 0.25
0.36 0.65
0.38 0.38
0.091 0.091
    H1000’s







    H2000’s -14 (-29 to 1.3)

-0.16 (-0.74 to 0.42)

0.30 (-0.19 to 0.79)

0.87 (0.00 to 1.7)

    H3000’s -9.6 (-24 to 5.0)

0.29 (-0.28 to 0.86)

0.28 (-0.20 to 0.76)

0.73 (-0.11 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.73 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

0.99 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.5 (-21 to 34) 0.64 0.78 0.76 (-0.02 to 1.5) 0.056 0.17 -0.58 (-1.1 to -0.10) 0.017 0.052 0.86 (0.20 to 1.5) 0.011 0.033
mean_StanceDur -2.8 (-22 to 17) 0.78 0.78 -0.39 (-0.94 to 0.16) 0.16 0.24 -0.10 (-0.38 to 0.18) 0.47 0.57 0.25 (-0.03 to 0.53) 0.081 0.081
group_char
0.34 0.78
0.42 0.42
0.57 0.57
0.066 0.081
    H1000’s







    H2000’s -14 (-35 to 6.9)

-0.24 (-0.84 to 0.35)

0.28 (-0.25 to 0.81)

0.92 (0.03 to 1.8)

    H3000’s -0.20 (-21 to 21)

0.17 (-0.42 to 0.76)

0.18 (-0.34 to 0.70)

0.84 (-0.03 to 1.7)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.79 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 72 (NA to NA)

2.1 (NA to NA)

1.0 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 7.7 (-24 to 40) 0.64 0.76 0.81 (-0.10 to 1.7) 0.081 0.24 -0.53 (-1.1 to 0.02) 0.057 0.17 0.78 (0.07 to 1.5) 0.031 0.078
mean_GaitCycleDur -2.5 (-19 to 14) 0.76 0.76 -0.30 (-0.76 to 0.16) 0.20 0.30 -0.10 (-0.33 to 0.13) 0.40 0.60 0.21 (-0.02 to 0.45) 0.078 0.078
group_char
0.34 0.76
0.44 0.44
0.60 0.60
0.062 0.078
    H1000’s







    H2000’s -14 (-35 to 6.8)

-0.25 (-0.85 to 0.35)

0.27 (-0.26 to 0.80)

0.93 (0.03 to 1.8)

    H3000’s -0.49 (-22 to 21)

0.16 (-0.45 to 0.76)

0.16 (-0.36 to 0.69)

0.86 (-0.01 to 1.7)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.79 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 72 (NA to NA)

2.1 (NA to NA)

1.0 (NA to NA)

1.0 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 8
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.6 (-22 to 8.9) 0.40 0.40 0.01 (-0.60 to 0.61) 0.98 0.98 -0.81 (-1.2 to -0.42) <0.001 <0.001 1.4 (0.84 to 2.0) <0.001 <0.001
mean_PeakUpDownVel_mean 41 (-11 to 93) 0.12 0.21 1.1 (-0.93 to 3.1) 0.29 0.57 0.42 (-0.54 to 1.4) 0.39 0.40 -1.1 (-2.2 to -0.11) 0.030 0.045
group_char
0.14 0.21
0.38 0.57
0.40 0.40
0.081 0.081
    H1000’s







    H2000’s -14 (-29 to 0.72)

-0.18 (-0.76 to 0.41)

0.29 (-0.20 to 0.78)

0.89 (0.02 to 1.8)

    H3000’s -10 (-25 to 4.4)

0.26 (-0.31 to 0.83)

0.28 (-0.21 to 0.76)

0.76 (-0.09 to 1.6)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.73 (NA to NA)

1.5 (NA to NA)

Residual.sd__Observation 53 (NA to NA)

2.1 (NA to NA)

0.93 (NA to NA)

0.99 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -5.7 (-16 to 4.7) 0.28 0.49 5.2 (-2.8 to 13) 0.20 0.61 -0.27 (-0.90 to 0.36) 0.40 0.60 1.4 (0.62 to 2.2) <0.001 0.001
mean_APexc_COV 0.04 (-0.51 to 0.59) 0.87 0.87 -0.18 (-0.59 to 0.24) 0.41 0.61 0.01 (-0.02 to 0.04) 0.40 0.60 -0.03 (-0.06 to 0.01) 0.14 0.21
group_char
0.33 0.49
0.82 0.82
0.91 0.91
0.32 0.32
    H1000’s







    H2000’s 7.0 (-2.3 to 16)

-0.55 (-8.0 to 6.9)

-0.14 (-0.76 to 0.48)

0.64 (-0.21 to 1.5)

    H3000’s 5.2 (-4.0 to 14)

1.6 (-5.8 to 8.9)

-0.10 (-0.70 to 0.50)

0.20 (-0.61 to 1.0)

subj_char.sd__(Intercept) 2.6 (NA to NA)

4.6 (NA to NA)

0.50 (NA to NA)

0.87 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -1.2 (-14 to 12) 0.86 0.86 -3.3 (-13 to 6.6) 0.51 0.76 0.05 (-0.71 to 0.81) 0.89 0.97 1.3 (0.43 to 2.2) 0.004 0.011
mean_APexc_mean -67 (-278 to 143) 0.53 0.80 102 (-52 to 256) 0.20 0.59 -2.0 (-13 to 9.5) 0.73 0.97 -5.6 (-18 to 6.4) 0.36 0.46
group_char
0.36 0.80
0.82 0.82
0.97 0.97
0.46 0.46
    H1000’s







    H2000’s 6.4 (-2.6 to 15)

-0.35 (-7.4 to 6.7)

-0.08 (-0.67 to 0.52)

0.40 (-0.44 to 1.2)

    H3000’s 4.5 (-3.9 to 13)

1.6 (-5.0 to 8.2)

-0.02 (-0.57 to 0.54)

-0.09 (-0.87 to 0.69)

subj_char.sd__(Intercept) 2.1 (NA to NA)

3.9 (NA to NA)

0.47 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -8.5 (-20 to 3.0) 0.15 0.29 5.8 (-3.1 to 15) 0.20 0.57 -0.48 (-1.2 to 0.21) 0.17 0.25 1.3 (0.42 to 2.1) 0.003 0.010
mean_MLexc_COV 0.24 (-0.43 to 0.90) 0.49 0.49 -0.22 (-0.73 to 0.28) 0.38 0.57 0.03 (-0.01 to 0.07) 0.14 0.25 -0.02 (-0.06 to 0.02) 0.41 0.41
group_char
0.19 0.29
0.87 0.87
0.95 0.95
0.41 0.41
    H1000’s







    H2000’s 7.3 (-1.2 to 16)

-1.7 (-8.7 to 5.2)

-0.05 (-0.62 to 0.53)

0.47 (-0.35 to 1.3)

    H3000’s 5.8 (-2.1 to 14)

-0.17 (-6.6 to 6.3)

0.05 (-0.49 to 0.59)

-0.03 (-0.79 to 0.73)

subj_char.sd__(Intercept) 2.3 (NA to NA)

4.5 (NA to NA)

0.49 (NA to NA)

0.87 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.6 (-12 to 7.1) 0.60 0.60 -1.3 (-8.7 to 6.0) 0.72 0.85 0.15 (-0.43 to 0.73) 0.61 0.91 1.0 (0.30 to 1.7) 0.006 0.017
mean_MLexc_mean -30 (-127 to 67) 0.55 0.60 47 (-24 to 119) 0.20 0.59 -2.7 (-8.0 to 2.7) 0.33 0.91 -0.36 (-6.0 to 5.3) 0.90 0.90
group_char
0.18 0.55
0.85 0.85
0.96 0.96
0.43 0.65
    H1000’s







    H2000’s 7.4 (-1.1 to 16)

-1.9 (-8.7 to 4.9)

-0.04 (-0.61 to 0.54)

0.47 (-0.35 to 1.3)

    H3000’s 5.9 (-2.1 to 14)

-0.47 (-6.8 to 5.9)

0.05 (-0.49 to 0.58)

-0.01 (-0.77 to 0.76)

subj_char.sd__(Intercept) 2.2 (NA to NA)

4.2 (NA to NA)

0.48 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.6 (-20 to 6.6) 0.33 0.49 -3.4 (-13 to 6.3) 0.49 0.74 0.09 (-0.64 to 0.83) 0.80 0.96 1.3 (0.51 to 2.2) 0.002 0.005
mean_StepDur 1.7 (-11 to 14) 0.79 0.79 6.3 (-2.9 to 15) 0.18 0.54 -0.17 (-0.83 to 0.50) 0.62 0.96 -0.38 (-1.1 to 0.29) 0.27 0.40
group_char
0.21 0.49
0.80 0.80
0.96 0.96
0.44 0.44
    H1000’s







    H2000’s 7.6 (-1.2 to 16)

-0.56 (-7.5 to 6.4)

-0.08 (-0.66 to 0.51)

0.40 (-0.43 to 1.2)

    H3000’s 6.0 (-2.4 to 14)

1.6 (-5.0 to 8.2)

-0.03 (-0.58 to 0.52)

-0.10 (-0.88 to 0.68)

subj_char.sd__(Intercept) 2.3 (NA to NA)

4.0 (NA to NA)

0.48 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -5.2 (-15 to 4.4) 0.29 0.43 -1.6 (-8.8 to 5.7) 0.67 0.81 0.09 (-0.48 to 0.65) 0.77 0.97 1.1 (0.42 to 1.8) 0.002 0.005
mean_UDexc_COV 0.01 (-0.60 to 0.63) 0.96 0.96 0.33 (-0.12 to 0.77) 0.15 0.46 -0.01 (-0.04 to 0.02) 0.48 0.97 -0.01 (-0.04 to 0.02) 0.55 0.55
group_char
0.21 0.43
0.81 0.81
0.97 0.97
0.42 0.55
    H1000’s







    H2000’s 7.2 (-1.3 to 16)

-2.2 (-9.0 to 4.7)

-0.03 (-0.61 to 0.54)

0.49 (-0.34 to 1.3)

    H3000’s 5.5 (-2.5 to 13)

-0.40 (-6.8 to 6.0)

0.03 (-0.50 to 0.57)

0.01 (-0.76 to 0.77)

subj_char.sd__(Intercept) 2.3 (NA to NA)

4.3 (NA to NA)

0.48 (NA to NA)

0.87 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -4.8 (-15 to 5.5) 0.36 0.54 6.9 (-0.88 to 15) 0.083 0.25 -0.34 (-0.94 to 0.26) 0.27 0.40 1.0 (0.30 to 1.8) 0.006 0.018
mean_UDexc_mean -8.6 (-363 to 346) 0.96 0.96 -182 (-441 to 76) 0.17 0.25 11 (-7.6 to 31) 0.24 0.40 -1.8 (-22 to 18) 0.86 0.86
group_char
0.20 0.54
0.80 0.80
0.99 0.99
0.43 0.65
    H1000’s







    H2000’s 7.2 (-1.3 to 16)

-1.8 (-8.6 to 5.0)

-0.04 (-0.61 to 0.52)

0.47 (-0.35 to 1.3)

    H3000’s 5.5 (-2.4 to 13)

0.29 (-6.0 to 6.6)

0.00 (-0.52 to 0.53)

-0.01 (-0.77 to 0.76)

subj_char.sd__(Intercept) 2.4 (NA to NA)

4.2 (NA to NA)

0.46 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.7 (-18 to 4.7) 0.25 0.37 -2.1 (-11 to 6.3) 0.62 0.82 0.05 (-0.59 to 0.69) 0.88 0.97 1.3 (0.56 to 2.1) <0.001 0.002
mean_StanceDur 1.3 (-6.3 to 8.9) 0.74 0.74 3.6 (-1.9 to 9.1) 0.20 0.60 -0.09 (-0.48 to 0.31) 0.67 0.97 -0.25 (-0.65 to 0.15) 0.22 0.33
group_char
0.19 0.37
0.82 0.82
0.97 0.97
0.44 0.44
    H1000’s







    H2000’s 7.6 (-1.1 to 16)

-0.77 (-7.7 to 6.1)

-0.07 (-0.65 to 0.51)

0.41 (-0.42 to 1.2)

    H3000’s 6.0 (-2.2 to 14)

1.3 (-5.2 to 7.8)

-0.02 (-0.56 to 0.53)

-0.10 (-0.87 to 0.68)

subj_char.sd__(Intercept) 2.3 (NA to NA)

4.0 (NA to NA)

0.48 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.6 (-20 to 6.6) 0.33 0.49 -3.4 (-13 to 6.3) 0.49 0.74 0.09 (-0.64 to 0.83) 0.80 0.96 1.4 (0.51 to 2.2) 0.002 0.005
mean_GaitCycleDur 0.86 (-5.5 to 7.2) 0.79 0.79 3.1 (-1.4 to 7.7) 0.18 0.54 -0.08 (-0.42 to 0.25) 0.62 0.96 -0.19 (-0.53 to 0.14) 0.26 0.40
group_char
0.21 0.49
0.80 0.80
0.96 0.96
0.44 0.44
    H1000’s







    H2000’s 7.6 (-1.2 to 16)

-0.56 (-7.5 to 6.4)

-0.08 (-0.66 to 0.51)

0.40 (-0.43 to 1.2)

    H3000’s 6.0 (-2.4 to 14)

1.6 (-5.0 to 8.2)

-0.03 (-0.58 to 0.52)

-0.10 (-0.88 to 0.68)

subj_char.sd__(Intercept) 2.3 (NA to NA)

4.0 (NA to NA)

0.48 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 9
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.0 (-15 to 2.8) 0.18 0.32 5.9 (-0.70 to 13) 0.080 0.24 -0.17 (-0.69 to 0.35) 0.52 0.81 1.0 (0.35 to 1.7) 0.003 0.008
mean_PeakUpDownVel_mean 4.0 (-24 to 32) 0.78 0.78 -14 (-35 to 5.6) 0.16 0.24 0.46 (-1.0 to 1.9) 0.54 0.81 -0.09 (-1.6 to 1.4) 0.91 0.91
group_char
0.21 0.32
0.84 0.84
0.97 0.97
0.43 0.64
    H1000’s







    H2000’s 7.2 (-1.4 to 16)

-1.5 (-8.2 to 5.3)

-0.06 (-0.63 to 0.52)

0.47 (-0.35 to 1.3)

    H3000’s 5.4 (-2.5 to 13)

0.45 (-5.8 to 6.7)

0.00 (-0.53 to 0.53)

-0.01 (-0.77 to 0.76)

subj_char.sd__(Intercept) 2.5 (NA to NA)

4.0 (NA to NA)

0.47 (NA to NA)

0.88 (NA to NA)

Residual.sd__Observation 21 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

1.1 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.3 (-5.6 to 18) 0.30 0.45 0.60 (-7.8 to 9.0) 0.89 0.94 0.08 (-0.62 to 0.79) 0.81 0.81 0.25 (-0.44 to 0.95) 0.48 0.48
mean_APexc_COV -0.17 (-0.78 to 0.44) 0.58 0.58 0.01 (-0.38 to 0.41) 0.94 0.94 -0.02 (-0.05 to 0.02) 0.33 0.81 0.03 (0.00 to 0.05) 0.083 0.12
group_char
0.016 0.048
0.38 0.94
0.69 0.81
0.052 0.12
    H1000’s







    H2000’s -9.6 (-20 to 0.93)

3.8 (-4.8 to 12)

0.26 (-0.47 to 0.99)

0.97 (0.16 to 1.8)

    H3000’s 5.4 (-5.2 to 16)

-2.2 (-10 to 6.0)

0.27 (-0.42 to 0.97)

0.65 (-0.11 to 1.4)

subj_char.sd__(Intercept) 6.9 (NA to NA)

8.7 (NA to NA)

0.77 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 18 (4.3 to 32) 0.010 0.015 1.0 (-8.2 to 10) 0.83 0.97 0.19 (-0.57 to 0.95) 0.62 0.93 0.38 (-0.36 to 1.1) 0.31 0.31
mean_APexc_mean -273 (-502 to -44) 0.019 0.019 -2.7 (-144 to 139) 0.97 0.97 -7.1 (-19 to 4.6) 0.23 0.70 5.6 (-4.4 to 16) 0.27 0.31
group_char
0.009 0.015
0.37 0.97
0.97 0.97
0.007 0.021
    H1000’s







    H2000’s -14 (-24 to -3.4)

3.8 (-4.7 to 12)

0.09 (-0.62 to 0.81)

1.2 (0.35 to 2.0)

    H3000’s 0.66 (-8.4 to 9.8)

-2.1 (-9.5 to 5.3)

0.04 (-0.59 to 0.67)

0.96 (0.23 to 1.7)

subj_char.sd__(Intercept) 6.7 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.9 (-11 to 15) 0.77 0.78 -3.0 (-12 to 5.9) 0.51 0.51 0.52 (-0.21 to 1.3) 0.16 0.24 0.55 (-0.19 to 1.3) 0.14 0.22
mean_MLexc_COV 0.11 (-0.67 to 0.89) 0.78 0.78 0.26 (-0.24 to 0.76) 0.30 0.49 -0.05 (-0.09 to -0.01) 0.018 0.055 0.01 (-0.03 to 0.05) 0.63 0.63
group_char
0.021 0.064
0.33 0.49
0.92 0.92
0.010 0.030
    H1000’s







    H2000’s -10 (-20 to -0.18)

4.3 (-4.1 to 13)

0.10 (-0.61 to 0.80)

1.1 (0.30 to 1.9)

    H3000’s 3.8 (-5.0 to 13)

-2.1 (-9.3 to 5.2)

0.12 (-0.49 to 0.73)

0.89 (0.18 to 1.6)

subj_char.sd__(Intercept) 6.7 (NA to NA)

8.8 (NA to NA)

0.75 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 13 (2.8 to 24) 0.013 0.021 6.7 (-0.56 to 14) 0.071 0.11 -0.28 (-0.89 to 0.33) 0.37 0.88 0.46 (-0.17 to 1.1) 0.15 0.23
mean_MLexc_mean -120 (-222 to -19) 0.020 0.021 -72 (-135 to -8.8) 0.026 0.077 1.2 (-4.1 to 6.5) 0.67 0.88 2.7 (-1.8 to 7.3) 0.24 0.24
group_char
0.021 0.021
0.36 0.36
0.88 0.88
0.012 0.037
    H1000’s







    H2000’s -9.7 (-20 to 0.45)

4.3 (-3.9 to 12)

0.17 (-0.53 to 0.87)

1.1 (0.27 to 1.9)

    H3000’s 4.5 (-4.4 to 13)

-1.6 (-8.8 to 5.6)

0.11 (-0.50 to 0.72)

0.88 (0.16 to 1.6)

subj_char.sd__(Intercept) 7.4 (NA to NA)

8.6 (NA to NA)

0.74 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 16 (2.0 to 30) 0.025 0.038 4.1 (-5.0 to 13) 0.38 0.39 -0.13 (-0.88 to 0.62) 0.73 0.89 0.31 (-0.41 to 1.0) 0.40 0.40
mean_StepDur -14 (-27 to -0.02) 0.050 0.050 -3.5 (-12 to 4.6) 0.39 0.39 -0.06 (-0.73 to 0.61) 0.87 0.89 0.41 (-0.15 to 0.97) 0.15 0.23
group_char
0.016 0.038
0.34 0.39
0.89 0.89
0.006 0.019
    H1000’s







    H2000’s -13 (-23 to -2.5)

3.3 (-5.1 to 12)

0.17 (-0.54 to 0.88)

1.2 (0.35 to 2.0)

    H3000’s 0.70 (-8.5 to 10)

-2.8 (-10 to 4.6)

0.11 (-0.52 to 0.74)

0.98 (0.25 to 1.7)

subj_char.sd__(Intercept) 6.9 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 13 (3.4 to 24) 0.009 0.015 2.5 (-4.6 to 9.7) 0.48 0.49 -0.27 (-0.86 to 0.33) 0.37 0.88 0.38 (-0.23 to 0.99) 0.22 0.22
mean_UDexc_COV -0.79 (-1.4 to -0.16) 0.014 0.015 -0.13 (-0.52 to 0.25) 0.49 0.49 0.01 (-0.03 to 0.04) 0.68 0.88 0.02 (0.00 to 0.05) 0.083 0.12
group_char
0.015 0.015
0.38 0.49
0.88 0.88
0.012 0.036
    H1000’s







    H2000’s -10 (-20 to -0.11)

3.9 (-4.4 to 12)

0.18 (-0.53 to 0.88)

1.1 (0.28 to 1.9)

    H3000’s 4.5 (-4.2 to 13)

-1.9 (-9.2 to 5.3)

0.11 (-0.50 to 0.73)

0.87 (0.16 to 1.6)

subj_char.sd__(Intercept) 6.7 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -8.0 (-18 to 2.5) 0.13 0.13 -1.6 (-8.9 to 5.7) 0.67 0.67 0.11 (-0.50 to 0.72) 0.72 0.81 0.94 (0.32 to 1.6) 0.003 0.009
mean_UDexc_mean 508 (142 to 874) 0.007 0.020 108 (-117 to 334) 0.35 0.53 -13 (-32 to 5.4) 0.17 0.50 -12 (-27 to 4.2) 0.15 0.15
group_char
0.024 0.037
0.35 0.53
0.81 0.81
0.008 0.012
    H1000’s







    H2000’s -12 (-22 to -1.3)

3.6 (-4.7 to 12)

0.20 (-0.50 to 0.91)

1.1 (0.31 to 1.9)

    H3000’s 2.0 (-7.0 to 11)

-2.4 (-9.7 to 4.8)

0.16 (-0.46 to 0.79)

0.93 (0.22 to 1.6)

subj_char.sd__(Intercept) 7.6 (NA to NA)

8.7 (NA to NA)

0.76 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 13 (1.0 to 25) 0.033 0.050 3.5 (-4.4 to 11) 0.39 0.39 -0.15 (-0.81 to 0.52) 0.67 0.88 0.39 (-0.27 to 1.0) 0.25 0.25
mean_StanceDur -7.7 (-16 to 0.51) 0.066 0.066 -2.1 (-7.0 to 2.7) 0.39 0.39 -0.03 (-0.43 to 0.37) 0.88 0.88 0.23 (-0.10 to 0.57) 0.17 0.25
group_char
0.017 0.050
0.35 0.39
0.88 0.88
0.007 0.021
    H1000’s







    H2000’s -12 (-23 to -2.1)

3.3 (-5.0 to 12)

0.17 (-0.54 to 0.88)

1.2 (0.34 to 2.0)

    H3000’s 1.3 (-7.8 to 10)

-2.7 (-10 to 4.7)

0.11 (-0.52 to 0.74)

0.96 (0.24 to 1.7)

subj_char.sd__(Intercept) 6.9 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 16 (2.1 to 30) 0.024 0.036 4.0 (-5.0 to 13) 0.38 0.39 -0.13 (-0.88 to 0.62) 0.73 0.89 0.31 (-0.41 to 1.0) 0.40 0.40
mean_GaitCycleDur -6.9 (-14 to -0.06) 0.048 0.048 -1.8 (-5.8 to 2.3) 0.39 0.39 -0.03 (-0.36 to 0.31) 0.87 0.89 0.20 (-0.08 to 0.48) 0.15 0.23
group_char
0.016 0.036
0.34 0.39
0.89 0.89
0.006 0.019
    H1000’s







    H2000’s -13 (-23 to -2.5)

3.3 (-5.1 to 12)

0.17 (-0.54 to 0.88)

1.2 (0.35 to 2.0)

    H3000’s 0.69 (-8.6 to 9.9)

-2.8 (-10 to 4.6)

0.11 (-0.52 to 0.74)

0.98 (0.25 to 1.7)

subj_char.sd__(Intercept) 6.9 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.98 (NA to NA)

Residual.sd__Observation 23 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.90 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 10
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -6.7 (-15 to 2.1) 0.13 0.13 -1.0 (-7.4 to 5.4) 0.75 0.75 0.05 (-0.48 to 0.59) 0.84 0.84 0.84 (0.26 to 1.4) 0.004 0.013
mean_PeakUpDownVel_mean 44 (17 to 71) 0.001 0.003 8.2 (-8.1 to 25) 0.32 0.53 -1.0 (-2.4 to 0.29) 0.13 0.38 -0.68 (-1.8 to 0.45) 0.24 0.24
group_char
0.018 0.027
0.35 0.53
0.80 0.84
0.008 0.013
    H1000’s







    H2000’s -12 (-22 to -2.0)

3.6 (-4.7 to 12)

0.21 (-0.49 to 0.92)

1.1 (0.31 to 1.9)

    H3000’s 1.5 (-7.3 to 10)

-2.5 (-9.8 to 4.8)

0.17 (-0.45 to 0.79)

0.93 (0.21 to 1.6)

subj_char.sd__(Intercept) 7.0 (NA to NA)

8.7 (NA to NA)

0.75 (NA to NA)

0.97 (NA to NA)

Residual.sd__Observation 22 (NA to NA)

13 (NA to NA)

1.1 (NA to NA)

0.91 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -17 (-50 to 16) 0.32 0.32 3.3 (-2.1 to 8.7) 0.23 0.64 -0.51 (-1.0 to 0.01) 0.056 0.17 0.53 (-0.18 to 1.2) 0.15 0.22
mean_APexc_COV 1.2 (-0.60 to 3.0) 0.19 0.32 -0.07 (-0.37 to 0.22) 0.64 0.64 0.02 (-0.01 to 0.04) 0.21 0.27 0.00 (-0.03 to 0.03) 0.93 0.93
group_char
0.26 0.32
0.48 0.64
0.27 0.27
0.002 0.005
    H1000’s







    H2000’s -17 (-44 to 10)

-2.0 (-6.5 to 2.4)

-0.24 (-0.72 to 0.24)

1.3 (0.56 to 2.0)

    H3000’s -26 (-58 to 5.7)

0.22 (-5.0 to 5.4)

-0.45 (-0.98 to 0.09)

1.1 (0.26 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -5.1 (-47 to 36) 0.81 0.81 0.35 (-6.4 to 7.1) 0.92 0.92 -0.20 (-0.82 to 0.41) 0.52 0.81 0.38 (-0.42 to 1.2) 0.35 0.53
mean_APexc_mean 137 (-564 to 839) 0.70 0.81 34 (-80 to 148) 0.56 0.84 -0.71 (-11 to 9.1) 0.89 0.89 3.1 (-8.9 to 15) 0.61 0.61
group_char
0.72 0.81
0.51 0.84
0.54 0.81
<0.001 0.001
    H1000’s







    H2000’s -8.1 (-34 to 18)

-2.1 (-6.3 to 2.0)

-0.14 (-0.60 to 0.32)

1.3 (0.62 to 2.0)

    H3000’s -11 (-37 to 16)

-0.08 (-4.4 to 4.3)

-0.27 (-0.74 to 0.20)

1.1 (0.40 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -8.9 (-44 to 27) 0.63 0.63 3.4 (-2.3 to 9.2) 0.24 0.63 0.00 (-0.54 to 0.53)
0.99
0.99
0.51 (-0.21 to 1.2) 0.16 0.24
mean_MLexc_COV 0.79 (-1.4 to 3.0) 0.49 0.63 -0.09 (-0.45 to 0.27) 0.63 0.63 -0.02 (-0.05 to 0.01) 0.28 0.84 0.00 (-0.03 to 0.04) 0.88 0.88
group_char
0.56 0.63
0.43 0.63
0.56 0.84
<0.001 0.001
    H1000’s







    H2000’s -9.1 (-34 to 16)

-2.5 (-6.5 to 1.5)

-0.14 (-0.59 to 0.31)

1.3 (0.60 to 2.0)

    H3000’s -13 (-38 to 11)

-0.52 (-4.5 to 3.5)

-0.24 (-0.69 to 0.21)

1.1 (0.37 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -0.12 (-30 to 29)
0.99
0.99
0.47 (-4.3 to 5.3) 0.85 0.85 -0.50 (-0.95 to -0.04) 0.034 0.10 0.60 (-0.03 to 1.2) 0.061 0.092
mean_MLexc_mean 30 (-269 to 328) 0.85
0.99
21 (-27 to 70) 0.39 0.59 3.1 (-1.0 to 7.3) 0.14 0.21 -0.64 (-5.7 to 4.4) 0.81 0.81
group_char
0.57
0.99

0.39 0.59
0.52 0.52
<0.001 0.001
    H1000’s







    H2000’s -9.8 (-35 to 15)

-2.7 (-6.7 to 1.3)

-0.17 (-0.62 to 0.29)

1.3 (0.60 to 2.0)

    H3000’s -13 (-37 to 12)

-0.60 (-4.6 to 3.4)

-0.26 (-0.71 to 0.19)

1.1 (0.38 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.6 (-44 to 39) 0.90 0.90 -0.25 (-7.0 to 6.5) 0.94 0.94 -0.28 (-0.87 to 0.30) 0.34 0.87 0.46 (-0.29 to 1.2) 0.23 0.35
mean_StepDur 5.4 (-37 to 47) 0.80 0.90 2.7 (-4.1 to 9.5) 0.44 0.73 0.05 (-0.50 to 0.60) 0.87 0.87 0.10 (-0.55 to 0.75) 0.77 0.77
group_char
0.68 0.90
0.49 0.73
0.59 0.87
<0.001 0.001
    H1000’s







    H2000’s -8.7 (-34 to 17)

-2.1 (-6.2 to 2.0)

-0.13 (-0.58 to 0.33)

1.3 (0.61 to 2.0)

    H3000’s -11 (-38 to 16)

0.11 (-4.3 to 4.5)

-0.24 (-0.71 to 0.23)

1.1 (0.38 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -11 (-40 to 19) 0.47 0.49 2.3 (-2.5 to 7.1) 0.36 0.68 -0.61 (-1.0 to -0.17) 0.007 0.020 0.49 (-0.13 to 1.1) 0.12 0.18
mean_UDexc_COV 1.0 (-0.88 to 3.0) 0.29 0.49 -0.01 (-0.32 to 0.31) 0.97 0.97 0.03 (0.00 to 0.05) 0.024 0.036 0.01 (-0.02 to 0.04) 0.73 0.73
group_char
0.49 0.49
0.45 0.68
0.39 0.39
<0.001 0.002
    H1000’s







    H2000’s -11 (-35 to 14)

-2.5 (-6.5 to 1.5)

-0.17 (-0.61 to 0.27)

1.3 (0.59 to 2.0)

    H3000’s -14 (-39 to 10)

-0.57 (-4.6 to 3.5)

-0.31 (-0.75 to 0.13)

1.1 (0.36 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.50 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 25 (-5.2 to 55) 0.10 0.16 1.3 (-3.6 to 6.2) 0.59 0.68 0.22 (-0.22 to 0.67) 0.33 0.49 0.66 (0.04 to 1.3) 0.038 0.057
mean_UDexc_mean -950 (-1,993 to 94) 0.074 0.16 36 (-135 to 207) 0.68 0.68 -20 (-34 to -5.7) 0.006 0.017 -4.6 (-22 to 12) 0.59 0.59
group_char
0.65 0.65
0.45 0.68
0.62 0.62
<0.001 0.001
    H1000’s







    H2000’s -9.2 (-34 to 15)

-2.5 (-6.5 to 1.5)

-0.13 (-0.56 to 0.31)

1.3 (0.60 to 2.0)

    H3000’s -11 (-35 to 14)

-0.66 (-4.7 to 3.4)

-0.22 (-0.65 to 0.22)

1.1 (0.38 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.49 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

0.99 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -1.6 (-37 to 34) 0.93 0.93 0.33 (-5.4 to 6.1) 0.91 0.91 -0.29 (-0.80 to 0.22) 0.26 0.79 0.51 (-0.17 to 1.2) 0.14 0.21
mean_StanceDur 3.2 (-22 to 28) 0.80 0.93 1.5 (-2.6 to 5.6) 0.47 0.73 0.04 (-0.29 to 0.37) 0.82 0.82 0.04 (-0.35 to 0.42) 0.86 0.86
group_char
0.66 0.93
0.49 0.73
0.59 0.82
<0.001 0.001
    H1000’s







    H2000’s -8.8 (-34 to 16)

-2.2 (-6.3 to 1.9)

-0.13 (-0.58 to 0.33)

1.3 (0.60 to 2.0)

    H3000’s -12 (-38 to 15)

-0.05 (-4.3 to 4.2)

-0.24 (-0.70 to 0.22)

1.1 (0.38 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -2.6 (-44 to 39) 0.90 0.90 -0.24 (-7.0 to 6.5) 0.94 0.94 -0.28 (-0.87 to 0.30) 0.34 0.87 0.46 (-0.29 to 1.2) 0.23 0.34
mean_GaitCycleDur 2.7 (-18 to 24) 0.80 0.90 1.3 (-2.1 to 4.7) 0.44 0.73 0.02 (-0.25 to 0.30) 0.87 0.87 0.05 (-0.27 to 0.37) 0.77 0.77
group_char
0.68 0.90
0.49 0.73
0.59 0.87
<0.001 0.001
    H1000’s







    H2000’s -8.7 (-34 to 17)

-2.1 (-6.2 to 2.0)

-0.13 (-0.58 to 0.33)

1.3 (0.61 to 2.0)

    H3000’s -11 (-38 to 16)

0.11 (-4.3 to 4.5)

-0.24 (-0.71 to 0.23)

1.1 (0.38 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

0.95 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 11
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 23 (-2.8 to 48) 0.081 0.12 1.7 (-2.5 to 5.9) 0.43 0.67 0.06 (-0.34 to 0.45) 0.77 0.77 0.63 (0.06 to 1.2) 0.030 0.045
mean_PeakUpDownVel_mean -87 (-169 to -5.2) 0.037 0.11 2.1 (-11 to 16) 0.77 0.77 -1.3 (-2.4 to -0.20) 0.020 0.060 -0.32 (-1.6 to 0.97) 0.63 0.63
group_char
0.75 0.75
0.44 0.67
0.69 0.77
<0.001 0.001
    H1000’s







    H2000’s -7.7 (-32 to 17)

-2.5 (-6.6 to 1.5)

-0.11 (-0.55 to 0.33)

1.3 (0.61 to 2.0)

    H3000’s -8.6 (-33 to 16)

-0.68 (-4.7 to 3.4)

-0.20 (-0.64 to 0.25)

1.1 (0.39 to 1.8)

subj_char.sd__(Intercept) 0.00 (NA to NA)

0.00 (NA to NA)

0.51 (NA to NA)

0.96 (NA to NA)

Residual.sd__Observation 79 (NA to NA)

13 (NA to NA)

1.0 (NA to NA)

1.2 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_avg_power for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.1 (-12 to 25) 0.52 0.52 0.14 (-6.2 to 6.5) 0.96 0.96 -0.60 (-1.2 to -0.05) 0.033 0.10 1.4 (0.55 to 2.2) 0.001 0.003
mean_APexc_COV -0.35 (-1.3 to 0.64) 0.49 0.52 -0.07 (-0.42 to 0.28) 0.68 0.96 0.01 (-0.01 to 0.04) 0.32 0.44 -0.01 (-0.04 to 0.02) 0.45 0.45
group_char
0.44 0.52
0.39 0.96
0.44 0.44
0.15 0.23
    H1000’s







    H2000’s -2.7 (-19 to 14)

3.8 (-1.6 to 9.1)

-0.17 (-0.69 to 0.34)

0.94 (-0.05 to 1.9)

    H3000’s 7.0 (-10 to 24)

2.0 (-3.6 to 7.7)

-0.34 (-0.87 to 0.18)

0.69 (-0.26 to 1.6)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.51 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in alpha_avg_power for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 9.3 (-11 to 30) 0.38 0.57 -2.0 (-9.3 to 5.4) 0.60 0.77 -0.68 (-1.3 to -0.07) 0.028 0.084 1.2 (0.42 to 2.1) 0.003 0.009
mean_APexc_mean -159 (-488 to 171) 0.35 0.57 18 (-103 to 139) 0.77 0.77 5.6 (-3.7 to 15) 0.24 0.36 -1.3 (-10 to 7.7) 0.78 0.78
group_char
0.58 0.58
0.40 0.77
0.87 0.87
0.21 0.32
    H1000’s







    H2000’s -6.3 (-22 to 9.1)

3.4 (-1.5 to 8.3)

-0.03 (-0.52 to 0.46)

0.85 (-0.12 to 1.8)

    H3000’s 1.4 (-13 to 16)

1.6 (-3.3 to 6.4)

-0.12 (-0.60 to 0.35)

0.56 (-0.36 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_avg_power for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 6.3 (-12 to 25) 0.51 0.51 0.94 (-5.6 to 7.5) 0.78 0.78 -0.40 (-0.96 to 0.16) 0.16 0.48 1.2 (0.42 to 2.0) 0.003 0.008
mean_MLexc_COV -0.38 (-1.5 to 0.68) 0.48 0.51 -0.13 (-0.51 to 0.25) 0.50 0.75 0.00 (-0.03 to 0.03) 0.91 0.91 0.00 (-0.03 to 0.03) 0.85 0.85
group_char
0.50 0.51
0.45 0.75
0.68 0.91
0.20 0.30
    H1000’s







    H2000’s -5.4 (-21 to 9.6)

3.1 (-1.7 to 8.0)

-0.07 (-0.55 to 0.41)

0.86 (-0.11 to 1.8)

    H3000’s 3.5 (-11 to 18)

1.3 (-3.3 to 5.8)

-0.20 (-0.65 to 0.25)

0.58 (-0.33 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in beta_div_theta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 2.8 (-13 to 18) 0.72 0.72 -1.2 (-6.6 to 4.2) 0.67 0.94 -0.59 (-1.1 to -0.12) 0.014 0.041 1.3 (0.56 to 2.0) <0.001 0.002
mean_MLexc_mean -28 (-178 to 122) 0.71 0.72 2.1 (-53 to 57) 0.94 0.94 2.7 (-1.5 to 6.9) 0.21 0.32 -1.5 (-5.6 to 2.6) 0.48 0.48
group_char
0.56 0.72
0.44 0.94
0.66 0.66
0.18 0.28
    H1000’s







    H2000’s -4.6 (-20 to 11)

3.2 (-1.7 to 8.2)

-0.12 (-0.61 to 0.37)

0.89 (-0.09 to 1.9)

    H3000’s 3.7 (-10 to 18)

1.3 (-3.2 to 5.9)

-0.21 (-0.66 to 0.24)

0.58 (-0.33 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.53 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in theta_div_beta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 5.6 (-15 to 26) 0.60 0.60 -1.0 (-8.6 to 6.5) 0.79
0.99
-0.64 (-1.2 to -0.04) 0.035 0.11 1.2 (0.41 to 2.0) 0.003 0.009
mean_StepDur -5.4 (-25 to 14) 0.59 0.60 0.04 (-7.4 to 7.5)
0.99
0.99
0.29 (-0.25 to 0.83) 0.30 0.45 -0.03 (-0.52 to 0.46) 0.90 0.90
group_char
0.55 0.60
0.43
0.99

0.86 0.86
0.21 0.31
    H1000’s







    H2000’s -5.9 (-21 to 9.4)

3.3 (-1.7 to 8.2)

-0.03 (-0.52 to 0.46)

0.86 (-0.12 to 1.8)

    H3000’s 2.2 (-13 to 17)

1.3 (-3.5 to 6.2)

-0.13 (-0.60 to 0.35)

0.57 (-0.35 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_beta_div_theta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) -0.34 (-16 to 15) 0.97 0.97 -1.2 (-6.6 to 4.2) 0.66 0.93 -0.55 (-1.0 to -0.10) 0.016 0.049 1.3 (0.55 to 2.0) <0.001 0.001
mean_UDexc_COV 0.07 (-0.86 to 1.0) 0.88 0.97 0.02 (-0.34 to 0.37) 0.93 0.93 0.01 (-0.01 to 0.04) 0.27 0.40 -0.01 (-0.03 to 0.02) 0.52 0.52
group_char
0.52 0.97
0.42 0.93
0.62 0.62
0.19 0.28
    H1000’s







    H2000’s -5.2 (-20 to 9.9)

3.2 (-1.6 to 8.1)

-0.09 (-0.57 to 0.39)

0.87 (-0.10 to 1.8)

    H3000’s 3.5 (-11 to 18)

1.3 (-3.3 to 5.9)

-0.22 (-0.67 to 0.23)

0.59 (-0.32 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in log_theta_div_beta for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 4.0 (-13 to 21) 0.64 0.64 -2.0 (-7.9 to 4.0) 0.52 0.71 -0.23 (-0.72 to 0.26) 0.35 0.68 1.2 (0.41 to 1.9) 0.002 0.007
mean_UDexc_mean -146 (-708 to 416) 0.61 0.64 40 (-169 to 250) 0.71 0.71 -6.0 (-22 to 9.7) 0.45 0.68 0.84 (-14 to 15) 0.91 0.91
group_char
0.53 0.64
0.44 0.71
0.68 0.68
0.20 0.30
    H1000’s







    H2000’s -4.8 (-20 to 10)

3.2 (-1.7 to 8.0)

-0.06 (-0.54 to 0.42)

0.86 (-0.11 to 1.8)

    H3000’s 3.7 (-10 to 18)

1.3 (-3.3 to 5.8)

-0.20 (-0.65 to 0.25)

0.58 (-0.33 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_exp for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 3.9 (-14 to 22) 0.67 0.67 -0.78 (-7.2 to 5.7) 0.81 0.94 -0.56 (-1.1 to -0.04) 0.035 0.10 1.2 (0.44 to 1.9) 0.002 0.006
mean_StanceDur -2.7 (-14 to 9.1) 0.66 0.67 -0.19 (-4.6 to 4.3) 0.94 0.94 0.15 (-0.17 to 0.47) 0.37 0.55 -0.01 (-0.30 to 0.28) 0.93 0.93
group_char
0.55 0.67
0.44 0.94
0.82 0.82
0.20 0.30
    H1000’s







    H2000’s -5.6 (-21 to 9.6)

3.2 (-1.7 to 8.1)

-0.04 (-0.53 to 0.45)

0.86 (-0.11 to 1.8)

    H3000’s 2.7 (-12 to 17)

1.2 (-3.5 to 6.0)

-0.14 (-0.61 to 0.32)

0.57 (-0.34 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in aperiodic_offset for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 5.6 (-15 to 26) 0.60 0.60 -1.1 (-8.6 to 6.5) 0.78 0.99 -0.64 (-1.2 to -0.04) 0.035 0.11 1.2 (0.41 to 2.0) 0.003 0.009
mean_GaitCycleDur -2.7 (-13 to 7.1) 0.58 0.60 0.02 (-3.7 to 3.7) 0.99 0.99 0.14 (-0.13 to 0.41) 0.30 0.44 -0.02 (-0.26 to 0.23) 0.90 0.90
group_char
0.55 0.60
0.43 0.99
0.86 0.86
0.20 0.31
    H1000’s







    H2000’s -5.9 (-21 to 9.4)

3.3 (-1.7 to 8.2)

-0.03 (-0.52 to 0.46)

0.86 (-0.12 to 1.8)

    H3000’s 2.2 (-13 to 17)

1.3 (-3.5 to 6.2)

-0.13 (-0.60 to 0.35)

0.57 (-0.35 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.54 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing
Changes in NA for Cluster: 12
Characteristic BETA/THETA THETA/BETA log10(BETA/THETA) log10(THETA/BETA)
Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2 Beta (95% CI)1 p-value q-value2
(Intercept) 1.3 (-13 to 16) 0.86 0.89 -1.8 (-6.8 to 3.2) 0.49 0.70 -0.22 (-0.65 to 0.20) 0.30 0.45 1.2 (0.48 to 1.9) <0.001 0.003
mean_PeakUpDownVel_mean -2.9 (-46 to 40) 0.89 0.89 3.2 (-13 to 19) 0.70 0.70 -0.63 (-1.8 to 0.55) 0.30 0.45 -0.04 (-1.1 to 1.0) 0.95 0.95
group_char
0.52 0.89
0.44 0.70
0.72 0.72
0.20 0.30
    H1000’s







    H2000’s -5.0 (-20 to 10)

3.2 (-1.7 to 8.0)

-0.06 (-0.54 to 0.42)

0.86 (-0.11 to 1.8)

    H3000’s 3.7 (-10 to 18)

1.2 (-3.3 to 5.8)

-0.18 (-0.63 to 0.27)

0.58 (-0.33 to 1.5)

subj_char.sd__(Intercept) 13 (NA to NA)

0.00 (NA to NA)

0.52 (NA to NA)

1.4 (NA to NA)

Residual.sd__Observation 39 (NA to NA)

15 (NA to NA)

1.1 (NA to NA)

0.95 (NA to NA)

1 CI = Confidence Interval
2 False discovery rate correction for multiple testing